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Computational Intelligence by Andries P. Engelbrecht

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1Wiki - Computational Intelligence Research Lab

Computational Intelligence Research Lab dumped with WikiTeam tools.

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  • Title: ➤  Wiki - Computational Intelligence Research Lab
  • Language: English

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The book is available for download in "web" format, the size of the file-s is: 0.07 Mbs, the file-s for this book were downloaded 12 times, the file-s went public at Sat Feb 08 2014.

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2Transactions On Computational Collective Intelligence XIX

Computational Intelligence Research Lab dumped with WikiTeam tools.

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  • Title: ➤  Transactions On Computational Collective Intelligence XIX
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The book is available for download in "texts" format, the size of the file-s is: 578.63 Mbs, the file-s for this book were downloaded 17 times, the file-s went public at Wed May 11 2022.

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3Computational Intelligence, III : Proceedings Of The International Symposium "Computational Intelligence 90", Milan, Italy, 24-28 September, 1990

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Computational Intelligence Research Lab dumped with WikiTeam tools.

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  • Title: ➤  Computational Intelligence, III : Proceedings Of The International Symposium "Computational Intelligence 90", Milan, Italy, 24-28 September, 1990
  • Author: ➤  
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 665.91 Mbs, the file-s for this book were downloaded 12 times, the file-s went public at Mon Mar 29 2021.

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4New Challenges In Computational Collective Intelligence

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  • Title: ➤  New Challenges In Computational Collective Intelligence
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 786.31 Mbs, the file-s for this book were downloaded 18 times, the file-s went public at Sat May 21 2022.

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5Computational Economics : A Perspective From Computational Intelligence

Computational Intelligence Research Lab dumped with WikiTeam tools.

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  • Title: ➤  Computational Economics : A Perspective From Computational Intelligence
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 857.90 Mbs, the file-s for this book were downloaded 13 times, the file-s went public at Wed Aug 02 2023.

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6Advances In Artificial Intelligence : 17th Conference Of The Canadian Society For Computational Studies Of Intelligence, Canadian AI 2004, London, Ontario, Canada, May 17-19, 2004 : Proceedings

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  • Title: ➤  Advances In Artificial Intelligence : 17th Conference Of The Canadian Society For Computational Studies Of Intelligence, Canadian AI 2004, London, Ontario, Canada, May 17-19, 2004 : Proceedings
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 313.89 Mbs, the file-s for this book were downloaded 1110 times, the file-s went public at Tue Dec 29 2015.

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7TCI 3371 - Computational Intelligence II

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Tri 1 2016/2017

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  • Title: ➤  TCI 3371 - Computational Intelligence II
  • Author: ➤  
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 0.91 Mbs, the file-s for this book were downloaded 15 times, the file-s went public at Sun May 05 2024.

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8TCI 3371 - Computational Intelligence 2

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Tri 1 2015/2016

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  • Title: ➤  TCI 3371 - Computational Intelligence 2
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 0.89 Mbs, the file-s for this book were downloaded 14 times, the file-s went public at Sun May 05 2024.

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9TCI 3121 - Computational Intelligence

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Tri 1 2019/2020

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  • Title: ➤  TCI 3121 - Computational Intelligence
  • Author: ➤  
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 0.94 Mbs, the file-s for this book were downloaded 13 times, the file-s went public at Sat May 04 2024.

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10Computational Intellingence [i.e. Intelligence] : Principles, Techniques, And Applications

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Tri 1 2019/2020

“Computational Intellingence [i.e. Intelligence] : Principles, Techniques, And Applications” Metadata:

  • Title: ➤  Computational Intellingence [i.e. Intelligence] : Principles, Techniques, And Applications
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The book is available for download in "texts" format, the size of the file-s is: 1084.73 Mbs, the file-s for this book were downloaded 129 times, the file-s went public at Sat May 09 2020.

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11Computational Intelligence In Design And Manufacturing

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Tri 1 2019/2020

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  • Title: ➤  Computational Intelligence In Design And Manufacturing
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 1265.35 Mbs, the file-s for this book were downloaded 26 times, the file-s went public at Sat Dec 17 2022.

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12Computational Intelligence In Information Assurance And Security

Tri 1 2019/2020

“Computational Intelligence In Information Assurance And Security” Metadata:

  • Title: ➤  Computational Intelligence In Information Assurance And Security
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 553.68 Mbs, the file-s for this book were downloaded 24 times, the file-s went public at Thu Jan 02 2020.

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13Computational Intelligence For Modelling And Prediction

Tri 1 2019/2020

“Computational Intelligence For Modelling And Prediction” Metadata:

  • Title: ➤  Computational Intelligence For Modelling And Prediction
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 889.90 Mbs, the file-s for this book were downloaded 21 times, the file-s went public at Thu Dec 19 2019.

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14Computational Intelligence For Deepwater Reservoir Depositional Environments Interpretation

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Predicting oil recovery efficiency of a deepwater reservoir is a challenging task. One approach to characterize a deepwater reservoir and to predict its producibility is by analyzing its depositional information. This research proposes a deposition-based stratigraphic interpretation framework for deepwater reservoir characterization. In this framework, one critical task is the identification and labeling of the stratigraphic components in the reservoir, according to their depositional environments. This interpretation process is labor intensive and can produce different results depending on the stratigrapher who performs the analysis. To relieve stratigrapher's workload and to produce more consistent results, we have developed a novel methodology to automate this process using various computational intelligence techniques. Using a well log data set, we demonstrate that the developed methodology and the designed workflow can produce finite state transducer models that interpret deepwater reservoir depositional environments adequately.

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  • Title: ➤  Computational Intelligence For Deepwater Reservoir Depositional Environments Interpretation
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 30.22 Mbs, the file-s for this book were downloaded 100 times, the file-s went public at Sat Sep 21 2013.

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15Advanced Computational Intelligence Paradigms In Healthcare 3

Predicting oil recovery efficiency of a deepwater reservoir is a challenging task. One approach to characterize a deepwater reservoir and to predict its producibility is by analyzing its depositional information. This research proposes a deposition-based stratigraphic interpretation framework for deepwater reservoir characterization. In this framework, one critical task is the identification and labeling of the stratigraphic components in the reservoir, according to their depositional environments. This interpretation process is labor intensive and can produce different results depending on the stratigrapher who performs the analysis. To relieve stratigrapher's workload and to produce more consistent results, we have developed a novel methodology to automate this process using various computational intelligence techniques. Using a well log data set, we demonstrate that the developed methodology and the designed workflow can produce finite state transducer models that interpret deepwater reservoir depositional environments adequately.

“Advanced Computational Intelligence Paradigms In Healthcare 3” Metadata:

  • Title: ➤  Advanced Computational Intelligence Paradigms In Healthcare 3
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 701.21 Mbs, the file-s for this book were downloaded 12 times, the file-s went public at Thu Jul 13 2023.

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16Militarized Conflict Modeling Using Computational Intelligence

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Predicting oil recovery efficiency of a deepwater reservoir is a challenging task. One approach to characterize a deepwater reservoir and to predict its producibility is by analyzing its depositional information. This research proposes a deposition-based stratigraphic interpretation framework for deepwater reservoir characterization. In this framework, one critical task is the identification and labeling of the stratigraphic components in the reservoir, according to their depositional environments. This interpretation process is labor intensive and can produce different results depending on the stratigrapher who performs the analysis. To relieve stratigrapher's workload and to produce more consistent results, we have developed a novel methodology to automate this process using various computational intelligence techniques. Using a well log data set, we demonstrate that the developed methodology and the designed workflow can produce finite state transducer models that interpret deepwater reservoir depositional environments adequately.

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  • Title: ➤  Militarized Conflict Modeling Using Computational Intelligence
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 678.27 Mbs, the file-s for this book were downloaded 19 times, the file-s went public at Thu Aug 11 2022.

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17Computational Intelligence In Bioinformatics

Predicting oil recovery efficiency of a deepwater reservoir is a challenging task. One approach to characterize a deepwater reservoir and to predict its producibility is by analyzing its depositional information. This research proposes a deposition-based stratigraphic interpretation framework for deepwater reservoir characterization. In this framework, one critical task is the identification and labeling of the stratigraphic components in the reservoir, according to their depositional environments. This interpretation process is labor intensive and can produce different results depending on the stratigrapher who performs the analysis. To relieve stratigrapher's workload and to produce more consistent results, we have developed a novel methodology to automate this process using various computational intelligence techniques. Using a well log data set, we demonstrate that the developed methodology and the designed workflow can produce finite state transducer models that interpret deepwater reservoir depositional environments adequately.

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  • Title: ➤  Computational Intelligence In Bioinformatics
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 971.68 Mbs, the file-s for this book were downloaded 25 times, the file-s went public at Fri Apr 22 2022.

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18Transactions On Computational Collective Intelligence XVII

pages cm

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  • Title: ➤  Transactions On Computational Collective Intelligence XVII
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 859.73 Mbs, the file-s for this book were downloaded 8 times, the file-s went public at Sat Sep 02 2023.

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19Fuzzy If-then Rules In Computational Intelligence : Theory And Applications

pages cm

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  • Title: ➤  Fuzzy If-then Rules In Computational Intelligence : Theory And Applications
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 1007.08 Mbs, the file-s for this book were downloaded 26 times, the file-s went public at Sat May 28 2022.

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20DTIC ADA546292: Computational Intelligence Applications For Defense

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This report reviews the priorities and discusses cognitive algorithms resulting in breakthroughs in defense applications, and making progress toward achieving AF goals. The mathematical techniques of dynamic logic and neural modeling fields model aspects of the functionality of the mind: perception, cognition, and higher cognitive functions. This leads to a significant improvement in classical signal processing applications, including detection, tracking, and fusion in noise and clutter, making autonomous situational awareness possible. The first part of this report describes past difficulties, why these problems have not been solved for decades, and the gist of the current approaches. The second part of this report addresses future research directions: the augmentation of human performance through improvements in man-machine interfaces. This includes modeling of language interacting with cognition. In future systems, computers will learn from humans, and humans will operate machines by language and thoughts..

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  • Title: ➤  DTIC ADA546292: Computational Intelligence Applications For Defense
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 17.05 Mbs, the file-s for this book were downloaded 65 times, the file-s went public at Mon Aug 20 2018.

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21Advances In Computational Intelligence : Theory And Practice

This report reviews the priorities and discusses cognitive algorithms resulting in breakthroughs in defense applications, and making progress toward achieving AF goals. The mathematical techniques of dynamic logic and neural modeling fields model aspects of the functionality of the mind: perception, cognition, and higher cognitive functions. This leads to a significant improvement in classical signal processing applications, including detection, tracking, and fusion in noise and clutter, making autonomous situational awareness possible. The first part of this report describes past difficulties, why these problems have not been solved for decades, and the gist of the current approaches. The second part of this report addresses future research directions: the augmentation of human performance through improvements in man-machine interfaces. This includes modeling of language interacting with cognition. In future systems, computers will learn from humans, and humans will operate machines by language and thoughts..

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  • Title: ➤  Advances In Computational Intelligence : Theory And Practice
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 965.81 Mbs, the file-s for this book were downloaded 6 times, the file-s went public at Sat Sep 23 2023.

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22Neuro-Fuzzy And Soft Computing: A Computational Approach To Learning And Machine Intelligence

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This report reviews the priorities and discusses cognitive algorithms resulting in breakthroughs in defense applications, and making progress toward achieving AF goals. The mathematical techniques of dynamic logic and neural modeling fields model aspects of the functionality of the mind: perception, cognition, and higher cognitive functions. This leads to a significant improvement in classical signal processing applications, including detection, tracking, and fusion in noise and clutter, making autonomous situational awareness possible. The first part of this report describes past difficulties, why these problems have not been solved for decades, and the gist of the current approaches. The second part of this report addresses future research directions: the augmentation of human performance through improvements in man-machine interfaces. This includes modeling of language interacting with cognition. In future systems, computers will learn from humans, and humans will operate machines by language and thoughts..

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  • Title: ➤  Neuro-Fuzzy And Soft Computing: A Computational Approach To Learning And Machine Intelligence
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The book is available for download in "texts" format, the size of the file-s is: 1704.74 Mbs, the file-s for this book were downloaded 66 times, the file-s went public at Fri Dec 09 2022.

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23Computational Intelligence 1994: Vol 10 Index

Computational Intelligence 1994: Volume 10 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1993-11_9_4 . Next issue: sim_computational-intelligence_1994-02_10_1 .

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  • Title: ➤  Computational Intelligence 1994: Vol 10 Index
  • Language: English

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24Machine Intelligence : Perspectives On The Computational Model

Computational Intelligence 1994: Volume 10 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1993-11_9_4 . Next issue: sim_computational-intelligence_1994-02_10_1 .

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25Computational Intelligence In Manufacturing Handbook

Computational Intelligence 1994: Volume 10 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1993-11_9_4 . Next issue: sim_computational-intelligence_1994-02_10_1 .

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26Studies In Computational Intelligence

Studies in Computational Intelligence is an active publication covering the theory, applications, and design methods of computational intelligence. It was established in 2005 and is published irregularly by Springer. The series covers a wide array of subjects, including neural networks, fuzzy systems, evolutionary computation, and artificial intelligence. It includes research articles, reviews, and monographs intended for academics, professionals, and students. Studies in Computational Intelligence can be found online at: https://www.springer.com/series/7092

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27Transactions On Computational Collective Intelligence XXI

Studies in Computational Intelligence is an active publication covering the theory, applications, and design methods of computational intelligence. It was established in 2005 and is published irregularly by Springer. The series covers a wide array of subjects, including neural networks, fuzzy systems, evolutionary computation, and artificial intelligence. It includes research articles, reviews, and monographs intended for academics, professionals, and students. Studies in Computational Intelligence can be found online at: https://www.springer.com/series/7092

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28NASA Technical Reports Server (NTRS) 19960047549: The NIST Real-Time Control System (RCS): A Reference Model Architecture For Computational Intelligence

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The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

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29Next Generation Computational Intelligence Microgrid

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Microgrid is a small power grid that localizes and operates independently of a larger grid to generate, distribute, and control the flow of energy. Microgrids provide efficient and reliable energy services to end users. Microgrid technology employs a wide range of distributed energy technologies including generation, storage, metering and communications. Microgrids manage energy generation, transmission, distribution, and usage on a small scale compared to conventional Microgrid.

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30Computational Semantics : An Introduction To Artificial Intelligence And Natural Language Comprehension

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31Computational And Ambient Intelligence : 9th International Work-Conference On Artificial Neural Networks, IWANN 2007, San Sebastian, Spain, June 20-22, 2007 : Proceedings

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Microgrid is a small power grid that localizes and operates independently of a larger grid to generate, distribute, and control the flow of energy. Microgrids provide efficient and reliable energy services to end users. Microgrid technology employs a wide range of distributed energy technologies including generation, storage, metering and communications. Microgrids manage energy generation, transmission, distribution, and usage on a small scale compared to conventional Microgrid.

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32Applying Computational Intelligence : How To Create Value

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Microgrid is a small power grid that localizes and operates independently of a larger grid to generate, distribute, and control the flow of energy. Microgrids provide efficient and reliable energy services to end users. Microgrid technology employs a wide range of distributed energy technologies including generation, storage, metering and communications. Microgrids manage energy generation, transmission, distribution, and usage on a small scale compared to conventional Microgrid.

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33Computational Intelligence Methods For Bioinformatics And Biostatistics

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34Computational Semantics : An Introduction To Artificial Intelligence And Natural Language Comprehension

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35Proceedings Of The Third IEEE Conference On Fuzzy Systems : IEEE World Congress On Computational Intelligence, June 26-June 29, 1994, Walt Disney World Dolphin Hotel, Orlando, Florida

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36An Anti-Skid Controller For Aircraft Applications Based On Computational Intelligence

The main purpose of this work is the development of an intelligent anti-skid braking system for business jet that would allow the maintenance of good performance during braking in all types of track conditions. In fact, one of the main problems in abs controllers modelling is due to the significantly variation of the optimal value of the friction coefficient closely related to the track conditions (dry, wet, icy); so it is extremely difficult to define a controller that ensures optimal braking performance in all environmental conditions. This study has involved the design of two controllers, based on computational intelligence techniques such as Artificial Neural Networks and Fuzzy Logic. In fact, AI is an excellent tool for the development of procedures dedicated to control systems which are complex and nonlinear like abs controllers. The application of these techniques seems particularly appropriate in the case of inadequate physical models as in the case of friction between wheels and track. The developed controllers make possible to operate in an unstable equilibrium point in order to achieve optimum braking performance.

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37The 1994 IEEE International Conference On Neural Networks : IEEE World Congress On Computational Intelligence, June 27-June 29, 1994, Walt Disney World Dolphin Hotel, Orlando Florida

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The main purpose of this work is the development of an intelligent anti-skid braking system for business jet that would allow the maintenance of good performance during braking in all types of track conditions. In fact, one of the main problems in abs controllers modelling is due to the significantly variation of the optimal value of the friction coefficient closely related to the track conditions (dry, wet, icy); so it is extremely difficult to define a controller that ensures optimal braking performance in all environmental conditions. This study has involved the design of two controllers, based on computational intelligence techniques such as Artificial Neural Networks and Fuzzy Logic. In fact, AI is an excellent tool for the development of procedures dedicated to control systems which are complex and nonlinear like abs controllers. The application of these techniques seems particularly appropriate in the case of inadequate physical models as in the case of friction between wheels and track. The developed controllers make possible to operate in an unstable equilibrium point in order to achieve optimum braking performance.

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38Imbalanced Dataset Classification Using Fuzzy ARTMAP And Computational Intelligence Techniques

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Recently, fuzzy adaptive resonance theory mapping (ARTMAP) neural networks are applied to solving complex problems due to their plasticity-stability capability and resonance property. An imbalanced dataset occurs when there is the presence of one class containing a greater number of instances than other classes. It is skewed representation of data. Many standard algorithms have failed in mitigating imbalanced dataset problems. There are four paradigms used-data level, algorithm level, cost-sensitive, and ensemble method in solving imbalanced dataset problems. Here we put forward a method to solve the imbalanced dataset problem by a brain-neuron framework and an ensemble of a special type of artificial neural network (ANN) called fuzzy ARTMAP thereafter we applied a clustering algorithm known as fuzzy C-means clustering to handle missing value and also propose to make fuzzy ARTMAP cost-sensitive. Results indicate 100% accuracy in classification.

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39Computational Intelligence For Engineering And Manufacturing

Recently, fuzzy adaptive resonance theory mapping (ARTMAP) neural networks are applied to solving complex problems due to their plasticity-stability capability and resonance property. An imbalanced dataset occurs when there is the presence of one class containing a greater number of instances than other classes. It is skewed representation of data. Many standard algorithms have failed in mitigating imbalanced dataset problems. There are four paradigms used-data level, algorithm level, cost-sensitive, and ensemble method in solving imbalanced dataset problems. Here we put forward a method to solve the imbalanced dataset problem by a brain-neuron framework and an ensemble of a special type of artificial neural network (ANN) called fuzzy ARTMAP thereafter we applied a clustering algorithm known as fuzzy C-means clustering to handle missing value and also propose to make fuzzy ARTMAP cost-sensitive. Results indicate 100% accuracy in classification.

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40Computational Intelligence 1985 - 1993: Vol 1-9 Index

Computational Intelligence 1985 - 1993: Volume 1-9 , Issue CUMULATIVE INDEX. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1994-11_10_4 . Next issue: sim_computational-intelligence_1995_11_index .

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41Computational Intelligence 1996: Vol 12 Index

Computational Intelligence 1996: Volume 12 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1995-11_11_4 . Next issue: sim_computational-intelligence_1996-02_12_1 .

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42Proceedings Of The First IEEE Conference On Evolutionary Computation : IEEE World Congress On Computational Intelligence, June 27-June 29, 1994, Walt Disney World Dolphin Hotel, Orlando, Florida

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Computational Intelligence 1996: Volume 12 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1995-11_11_4 . Next issue: sim_computational-intelligence_1996-02_12_1 .

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43Proceedings Of The Eighth Biennial Conference Of The Canadian Society For Computational Studies Of Intelligence, University Of Ottawa, Ottawa, Ontario, Canada 22-25 May 1990 = Actes De La Huitième Conférence Biennale De La Société Canadienne Pour L'étude De L'intelligence Par Ordinateur, Université D' Ottowa, Ottawa, Ontario, Canada 22-25 Mai 1990

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Computational Intelligence 1996: Volume 12 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1995-11_11_4 . Next issue: sim_computational-intelligence_1996-02_12_1 .

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“Proceedings Of The Eighth Biennial Conference Of The Canadian Society For Computational Studies Of Intelligence, University Of Ottawa, Ottawa, Ontario, Canada 22-25 May 1990 = Actes De La Huitième Conférence Biennale De La Société Canadienne Pour L'étude De L'intelligence Par Ordinateur, Université D' Ottowa, Ottawa, Ontario, Canada 22-25 Mai 1990” Subjects and Themes:

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44Computational Intelligence Paradigms : Theory And Applications Using MATLAB

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Computational Intelligence 1996: Volume 12 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1995-11_11_4 . Next issue: sim_computational-intelligence_1996-02_12_1 .

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45Computational Intelligence In Biomedical Engineering

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Computational Intelligence 1996: Volume 12 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1995-11_11_4 . Next issue: sim_computational-intelligence_1996-02_12_1 .

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46Emerging Biometrics: Deep Inference And Other Computational Intelligence

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This paper aims at identifying emerging computational intelligence trends for the design and modeling of complex biometric-enabled infrastructure and systems. Biometric-enabled systems are evolving towards deep learning and deep inference using the principles of adaptive computing, – the front tides of the modern computational intelligence domain. Therefore, we focus on intelligent inference engines widely deployed in biometrics. Computational intelligence applications that cover a wide spectrum of biometric tasks using physiological and behavioral traits are chosen for illustration. We highlight the technology gaps that must be addressed in future generations of biometric systems. The reported approaches and results primarily address the researchers who work towards developing the next generation of intelligent biometric-enabled systems.

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47Computational Intelligence Techniques For Tactile Sensing Systems.

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This article is from Sensors (Basel, Switzerland) , volume 14 . Abstract Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach.

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48Elevating Fraud Detection: Machine Learning Models With Computational Intelligence Optimization

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The amount of crimes committed online has undoubtedly increased as more people use the internet for e-commerce and other financial transactions. Machine learning algorithms have been created to detect payment fraud in online purchasing in order to address the issue. This study performs a thorough comparative examination of different metaheuristic optimizations as hyperparameter tuning methods; these are particle swarm optimization (PSO) and genetic algorithm (GA). They are used to optimize the receiver operating characteristic (ROC) area under the curve (AUC) of the three machine learning algorithms, namely X-gradient boost, random forest classifier, and light gradient boost machine. Since the study's data are unbalanced, the determined metrics were ROC AUC. PSO offers consistent conditions for finding the best solution, according to our experiment. Without the inclusion of population annihilation strategies, PSO can achieve the greatest results in various situations which are different from GA, a consistent condition for finding the best solution, according to our experiment. Without the inclusion of population annihilation strategies, PSO can achieve the greatest results in various situations. The findings indicate that random forest classifier provided the highest ROC AUC value both before and after the hyperparameter tuning process, with a score of 88.69% attained while utilizing PSO.

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49Computational Intelligence 1995: Vol 11 Index

Computational Intelligence 1995: Volume 11 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1985-1993_1-9_cumulative-index . Next issue: sim_computational-intelligence_1995-02_11_1 .

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50Bioinformatics Using Computational Intelligence Paradigms

Computational Intelligence 1995: Volume 11 , Issue Index. Digitized from IA1532821-01 . Previous issue: sim_computational-intelligence_1985-1993_1-9_cumulative-index . Next issue: sim_computational-intelligence_1995-02_11_1 .

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