作者: ADJ 時(shí)間: 2025-3-21 20:45 作者: 勛章 時(shí)間: 2025-3-22 02:53 作者: 印第安人 時(shí)間: 2025-3-22 06:27
Evolutionary Computing Algorithms,voted to discuss the possible applications of Genetic Algorithm in machine learning, intelligent search and derivative-free optimization problems. The chapter ends with a discussion on the scope of another evolutionary algorithm, popularly known as Genetic Programming.作者: Alopecia-Areata 時(shí)間: 2025-3-22 10:28
Behavioral Synergism of Soft Computing Tools,the integral effect of two or more computational models far exceeds their individual effects. A case study indicating the synergism of 2 different neural nets and GA has been undertaken in this chapter to study its application in motion planning of mobile robots.作者: FID 時(shí)間: 2025-3-22 12:57 作者: FID 時(shí)間: 2025-3-22 18:58
Textbook 2005al investigation, telecommunication networks, and intelligent robots. The book contains many numerical examples and homework problems with sufficient hints so that the students can solve them on their own..作者: concert 時(shí)間: 2025-3-23 00:18
al intelligence in a single volume in a lucid, precise and h.Computational Intelligence: Principles, Techniques and Applications. presents both theories and applications of computational intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects o作者: Mets552 時(shí)間: 2025-3-23 03:00 作者: 吼叫 時(shí)間: 2025-3-23 07:32 作者: alabaster 時(shí)間: 2025-3-23 10:01
Matrix elements for spherical Gaussians,of ADALINE neurons has been presented. The time required for training the neural net is insignificantly small. The scheme for the recognition of objects from their gray level images, using fuzzy ADALINE model, is translation-, rotation- and size- invariant.作者: hypnogram 時(shí)間: 2025-3-23 15:53
Fuzzy Databases and Possibilistic Reasoning, fuzzy relational databases. The chapter finally employs the above two concepts in the design of fuzzy relational databases. The concepts outlined in the chapter have been illustrated with many examples.作者: Emg827 時(shí)間: 2025-3-23 20:56
Competitive Learning Using Neural Nets, scope of realization of competition by Hebbian learning and the way-out to handle the limitation of Hebbian learning by Oja’s principle have been discussed in detail. The chapter also introduced principal component analysis and self-organizing feature models and examined their applications in face recognition problem.作者: 案發(fā)地點(diǎn) 時(shí)間: 2025-3-23 23:04
Object Recognition from Gray Images Using Fuzzy ADALINE Neurons,of ADALINE neurons has been presented. The time required for training the neural net is insignificantly small. The scheme for the recognition of objects from their gray level images, using fuzzy ADALINE model, is translation-, rotation- and size- invariant.作者: 格子架 時(shí)間: 2025-3-24 05:34 作者: Wordlist 時(shí)間: 2025-3-24 09:54 作者: 過份 時(shí)間: 2025-3-24 14:23
Benjamin Dufée,Etienne Mémin,Dan Crisanaries. Thus a pattern may be classified into one or more classes with a certain degree of membership to belong to each class. The algorithm for fuzzy pattern recognition is numerically illustrated, and its application in object recognition from real time video frames is also presented.作者: 忙碌 時(shí)間: 2025-3-24 16:27
Game Behavior Within the Intersection,ct of the chapter is the derivation of the classical back-propagation learning algorithm from the principles of gradient descent learning. The chapter ended with discussions on Radial Basis Function neural nets and modular neural nets.作者: GEST 時(shí)間: 2025-3-24 20:59
An Introduction to Computational Intelligence, the synergistic behavior of neuro-fuzzy, neuro-GA, neuro-belief and fuzzy-belief network models is also included in the chapter. A list of tutorial problems is appended at the end of the chapter to build up students’ ability in handling real world problems.作者: 魔鬼在游行 時(shí)間: 2025-3-25 02:41 作者: 保全 時(shí)間: 2025-3-25 06:08 作者: 外面 時(shí)間: 2025-3-25 09:22 作者: SPALL 時(shí)間: 2025-3-25 12:51 作者: Exposure 時(shí)間: 2025-3-25 19:46 作者: 指耕作 時(shí)間: 2025-3-25 23:06
Few-body problems in solid state physics,odel has extensive applications in diagnostic systems, where the probabilistic sensory data is fed at the leaves of the causal tree, and the root causes of system failure, which are denoted by non-terminal nodes in the network, are identified though an algorithm for belief propagation.作者: reject 時(shí)間: 2025-3-26 02:56 作者: 6Applepolish 時(shí)間: 2025-3-26 05:34
Few-body problems in solid state physics,ay be employed in complex decision-making and learning such as automated car driving in an accident-prone environment. The chapter also presented a new scheme for knowledge refinement by adaptation of weights in a fuzzy Petri net using a different form of Hebbian learning.作者: Osteons 時(shí)間: 2025-3-26 11:33
Fuzzy Logic and Approximate Reasoning,ingle and multiple antecedent clauses have been introduced in the chapter and the scope of one such reasoning scheme on a VLSI engine has been examined. The chapter ends with a discussion on the principles of fuzzy abductive reasoning.作者: Magnitude 時(shí)間: 2025-3-26 12:57 作者: 說笑 時(shí)間: 2025-3-26 17:09 作者: inhibit 時(shí)間: 2025-3-26 20:58
Machine Learning Using Fuzzy Petri Nets,ay be employed in complex decision-making and learning such as automated car driving in an accident-prone environment. The chapter also presented a new scheme for knowledge refinement by adaptation of weights in a fuzzy Petri net using a different form of Hebbian learning.作者: Eviction 時(shí)間: 2025-3-27 04:55
Textbook 2005, precise and highly comprehensive style. The textbook addresses the fundamental aspects of fuzzy sets and logic, neural networks, evolutionary computing and belief networks. The application areas include fuzzy databases, fuzzy control, image understanding, expert systems, object recognition, crimin作者: peptic-ulcer 時(shí)間: 2025-3-27 08:20 作者: 正式演說 時(shí)間: 2025-3-27 11:53
https://doi.org/10.1007/978-3-642-95696-6recognition. Finally, the chapter introduces fuzzy associative memory neural nets and outlines algorithms for pattern classification by the proposed neural nets. Concluding remarks are listed at the end of the chapter.作者: biosphere 時(shí)間: 2025-3-27 15:40
Matrix elements for spherical Gaussians,ples of the Q-learning algorithm have been illustrated with the well-known grid-world problem of mobile robots. The convergence analysis of the Q-learning algorithm is presented, and the scope of extension of the Q-learning algorithm in multi-agent learning systems has been addressed at the end of the chapter.作者: transdermal 時(shí)間: 2025-3-27 18:09 作者: Bmd955 時(shí)間: 2025-3-27 22:59 作者: 天然熱噴泉 時(shí)間: 2025-3-28 02:11 作者: Tailor 時(shí)間: 2025-3-28 09:06 作者: Insatiable 時(shí)間: 2025-3-28 13:34 作者: BILL 時(shí)間: 2025-3-28 16:35 作者: Spirometry 時(shí)間: 2025-3-28 19:28
Fuzzy Logic in Process Control,ds the scope of approximate reasoning of fuzzy logic in industrial process control systems. Two distinct models of fuzzy control namely Mamdani’s model and Takagi-Sugeno’s model have been discussed in this chapter with numerical illustrations. One important aspect of controller design for smart proc作者: Range-Of-Motion 時(shí)間: 2025-3-28 23:49
Fuzzy Pattern Recognition,tinctive features of the patterns are correctly identified, the classes can easily be distinguished in the feature space. Unfortunately, features in most pattern recognition problems are selected on an ad hoc basis, consequently causing the pattern classes to overlap, thereby leading to an ambiguity作者: debble 時(shí)間: 2025-3-29 05:16 作者: Mets552 時(shí)間: 2025-3-29 09:26 作者: 天然熱噴泉 時(shí)間: 2025-3-29 13:47
Supervised Neural Learning Algorithms,ts application in realization of binary logic functions. Rosenblatt’s perceptron learning algorithm designed for the McCulloch-Pitts neuronal model is presented next. Application of the perceptron learning model in both linear and nonlinear classification problems is then introduced. The chapter als作者: Pedagogy 時(shí)間: 2025-3-29 17:41 作者: hypnotic 時(shí)間: 2025-3-29 20:13
Competitive Learning Using Neural Nets,ng network having a noise-free input realized with an on-center off-surround configuration. An analysis of the model has been presented in detail. The scope of realization of competition by Hebbian learning and the way-out to handle the limitation of Hebbian learning by Oja’s principle have been dis作者: archenemy 時(shí)間: 2025-3-30 00:38 作者: Chromatic 時(shí)間: 2025-3-30 06:48
Evolutionary Computing Algorithms,optimization problems. After a brief introduction to this algorithm, the chapter provides a detailed discussion on one such algorithm, called Genetic Algorithm. An analysis of Genetic Algorithm by the well-known Schema theorem and Markov Chains is then presented. The latter part of the chapter is de作者: 承認(rèn) 時(shí)間: 2025-3-30 10:17 作者: 笨拙的我 時(shí)間: 2025-3-30 12:31 作者: COUCH 時(shí)間: 2025-3-30 17:38
Fuzzy Models for Face Matching and Mood Detection,s. These descriptors are estimated for three common kinds of image attributes namely edge, shade and mixed-range. The existing methods for matching of digital images, which are concerned with the comparison of the positions of directed edges, shades and mixed-range in an image with the same of anoth作者: Conclave 時(shí)間: 2025-3-30 21:18 作者: 捐助 時(shí)間: 2025-3-31 04:57 作者: 發(fā)芽 時(shí)間: 2025-3-31 06:35 作者: deface 時(shí)間: 2025-3-31 09:39
Machine Learning Using Fuzzy Petri Nets,ed learning process in the present context adapts the weights of the directed arcs from transition to places in the Petri net. A Hebbian type learning algorithm with a natural decay in weights is employed here to study the dynamic behavior of the algorithm. The algorithm is conditionally stable for 作者: 過去分詞 時(shí)間: 2025-3-31 16:40
Amit KonarFirst text on the subject that covers all aspects of computational intelligence.First to provide both theory and applications of computational intelligence in a single volume in a lucid, precise and h作者: foliage 時(shí)間: 2025-3-31 21:11 作者: Injunction 時(shí)間: 2025-4-1 00:47
Fuzzy Sets and Relations,d max-product composition operators. The extension principle of fuzzy sets and the concept of projection and cylindrical extension have been outlined in the chapter with examples. A brief introduction to fuzzy linguistic variables and fuzzy hedges is also given at the end of the chapter.作者: preeclampsia 時(shí)間: 2025-4-1 01:58 作者: Projection 時(shí)間: 2025-4-1 06:36 作者: Meditate 時(shí)間: 2025-4-1 10:52
