標題: Titlebook: Concepts of Soft Computing; Fuzzy and ANN with P Snehashish Chakraverty,Deepti Moyi Sahoo,Nisha Ran Textbook 2019 Springer Nature Singapore [打印本頁] 作者: 自由才謹慎 時間: 2025-3-21 20:02
書目名稱Concepts of Soft Computing影響因子(影響力)
書目名稱Concepts of Soft Computing影響因子(影響力)學(xué)科排名
書目名稱Concepts of Soft Computing網(wǎng)絡(luò)公開度
書目名稱Concepts of Soft Computing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Concepts of Soft Computing被引頻次
書目名稱Concepts of Soft Computing被引頻次學(xué)科排名
書目名稱Concepts of Soft Computing年度引用
書目名稱Concepts of Soft Computing年度引用學(xué)科排名
書目名稱Concepts of Soft Computing讀者反饋
書目名稱Concepts of Soft Computing讀者反饋學(xué)科排名
作者: Horizon 時間: 2025-3-21 22:40
rocesses..The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases.978-981-13-7430-2作者: 體貼 時間: 2025-3-22 03:40
Interval System of Linear Equationsfor handling uncertain parameters or values having infimum and supremum. In Chap. 1, the notion of interval matrix has been introduced and as such, this chapter deals with application of interval matrices for solving interval system of linear equations (ISLEs). Further, the chapter includes certain 作者: Heretical 時間: 2025-3-22 08:18 作者: 說不出 時間: 2025-3-22 08:58
: The Intermediate Value Theorem,terval eigenvalue problems.?Chapter 8 dealt with solving interval system of linear equations using interval analysis and in this chapter, we have focused on solving?eigenvalue problems having interval parameters.作者: Landlocked 時間: 2025-3-22 14:56 作者: Landlocked 時間: 2025-3-22 18:57
Convergence in Topological Spaces,eliminaries related to fuzzy sets, its membership function, and operaions of fuzzy sets have been discussed here. Further, C and/or MATLAB programming codes have been included for computational verification.作者: Ablation 時間: 2025-3-23 00:47
A Topological View of Sheaf Cohomology,sical real numbers and its arithmetic.?There exist different types of fuzzy numbers, but for the sake of completeness of the chapter, triangular, trapezoidal, and Gaussian fuzzy numbers based on the membership functions have only been included here. Further, the conversions of these fuzzy numbers to作者: 無動于衷 時間: 2025-3-23 02:20 作者: recede 時間: 2025-3-23 09:05
https://doi.org/10.1007/978-3-319-16958-3his book. Due to the involvement of such uncertainties, the parameters considered in real-world problems may be expressed as fuzzy sets instead of crisp sets. The methodology of transformation of a crisp set to appropriate fuzzy set is referred as ..?On the other hand, defuzzification may be conside作者: 輕觸 時間: 2025-3-23 11:47 作者: cochlea 時間: 2025-3-23 16:55
: The Intermediate Value Theorem,terval eigenvalue problems.?Chapter 8 dealt with solving interval system of linear equations using interval analysis and in this chapter, we have focused on solving?eigenvalue problems having interval parameters.作者: 精密 時間: 2025-3-23 18:42
Raymond F. Dickman,Peter FletcherN) because the processing is similar to the human brain. An ANN is composed of large number of highly interconnected processing elements called the neurons which work in union to solve different problems.?This chapter contains preliminaries of Artificial Neural Network,?types of neural network and?i作者: 變量 時間: 2025-3-23 23:58
Shape theory and covering spaces,euron allows binary activation (1 ON or 0 OFF), i.e., it either fires with an activation 1 or does not fire with an activation of 0. If w > 0, then the connected path is said to be excitatory else it is known as inhibitory. Excitatory connections have positive weights and inhibitory connections have作者: TAG 時間: 2025-3-24 06:20
,équivalence algébrique-analytique,at if two interconnected neurons are both “on” at the same time, then the weight between them should be increased. Hebbian network is a single layer neural network which consists of one input layer with many input units and one output layer with one output unit. This architecture is usually used for作者: 別炫耀 時間: 2025-3-24 09:14
Topos anneles et schemas relatifsrable. Single layer perceptron consists of one input layer with one or many input units and one output layer with one or many output units.?The present chapter describes about the single layer perceptron and its learning algorithm. The chapter also includes different Matlab program for calculating o作者: Chivalrous 時間: 2025-3-24 11:56
Toposes, Algebraic Geometry and Logic is a forward flow of information and no feedback between the layers. Such type of network is known as feedforward networks.?This chapter discusses?feedforward neural network, delta learning rule.?Error back propagation algorithm for unipolar and bipolar activation function are included in this chap作者: Distribution 時間: 2025-3-24 18:02 作者: Sad570 時間: 2025-3-24 22:51
http://image.papertrans.cn/c/image/234949.jpg作者: 易怒 時間: 2025-3-25 00:53 作者: PAEAN 時間: 2025-3-25 06:17 作者: Anecdote 時間: 2025-3-25 09:33 作者: Flat-Feet 時間: 2025-3-25 11:53 作者: 自傳 時間: 2025-3-25 16:23 作者: Decibel 時間: 2025-3-25 21:32 作者: PARA 時間: 2025-3-26 04:02
Fuzzy RelationsIn Chap.?., definitions and preliminaries related to crisp sets have been extended in terms of membership function for fuzzy sets. As such, the concept of crisp relations may also be extended to fuzzy relations. In this chapter, basically we will discuss the preliminaries related to fuzzy relations, operations, and compositions on fuzzy relations.作者: 傷心 時間: 2025-3-26 05:30 作者: colony 時間: 2025-3-26 09:05 作者: Plaque 時間: 2025-3-26 15:52 作者: mortgage 時間: 2025-3-26 20:02
Perceptron Learning Rulet chapter describes about the single layer perceptron and its learning algorithm. The chapter also includes different Matlab program for calculating output of various logic gates using perceptron learning algorithm.??作者: corn732 時間: 2025-3-27 00:29
Delta Learning Rule and Backpropagation Rule for Multilayer Perceptronedforward neural network, delta learning rule.?Error back propagation algorithm for unipolar and bipolar activation function are included in this chapter. Matlab program for calculating output for a multilayer neural network using error back propagation algorithm is?also given in the?chapter.作者: Torrid 時間: 2025-3-27 03:20
Convergence in Topological Spaces, also includes arithmetic operations for intervals and interval matrices. Further, the classical interval arithmetic has also been explained in this chapter along with corresponding C and MATLAB codes.作者: 母豬 時間: 2025-3-27 05:51
A Topological View of Sheaf Cohomology, fuzzy intervals with respect to the concept of intervals are also incorporated. In this regard, the interval arithmetic mentioned in Chap. 1 has been further extended to fuzzy intervals in this chapter.作者: calorie 時間: 2025-3-27 09:49 作者: zonules 時間: 2025-3-27 17:02
Raymond F. Dickman,Peter Fletcherts?architecture. This?chapter also discusses about the training or learning of neural network and about various?activation functions. Matlab programs have been done?for calculating different activation functions and?to calculate outputs if activation functions are?given.作者: Scintillations 時間: 2025-3-27 17:48
Shape theory and covering spaces, negative weights. Each neuron has a fixed threshold for firing. That is, if the net input to the neuron is greater than the threshold, it fires.?Different Matlab Programs have been done to generate output of various logical function using McCulloch-Pitt neural network algorithm.作者: Irrepressible 時間: 2025-3-27 22:25 作者: 祖?zhèn)?nbsp; 時間: 2025-3-28 05:38
Intervals also includes arithmetic operations for intervals and interval matrices. Further, the classical interval arithmetic has also been explained in this chapter along with corresponding C and MATLAB codes.作者: NORM 時間: 2025-3-28 07:38
Fuzzy Numbers fuzzy intervals with respect to the concept of intervals are also incorporated. In this regard, the interval arithmetic mentioned in Chap. 1 has been further extended to fuzzy intervals in this chapter.作者: Nonthreatening 時間: 2025-3-28 13:39 作者: 凝視 時間: 2025-3-28 15:25 作者: GRATE 時間: 2025-3-28 22:31 作者: 吸引人的花招 時間: 2025-3-28 23:58 作者: 可互換 時間: 2025-3-29 03:34
systems and eigenvalue problems for solving static and dynaThis book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computi作者: 從屬 時間: 2025-3-29 08:36
On the property of Kelley in hyperspaces,zy functions based on crisp relations along with the concepts of single and fuzzy bunch of crisp functions. Moreover, C or MATLAB codes related to fuzzy functions have also been included in this chapter.作者: Intact 時間: 2025-3-29 13:16 作者: 瘙癢 時間: 2025-3-29 17:48
Toposes, Algebraic Geometry and Logicedforward neural network, delta learning rule.?Error back propagation algorithm for unipolar and bipolar activation function are included in this chapter. Matlab program for calculating output for a multilayer neural network using error back propagation algorithm is?also given in the?chapter.作者: nullify 時間: 2025-3-29 20:54
Textbook 2019o attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership fun作者: Rct393 時間: 2025-3-30 03:20
Intervalsset theory and artificial neural network, that are discussed in subsequent chapters. In case of fuzzy sets, fuzzy number gets converted to interval form using .-cut as given in Chap. .. As such, preliminaries related to intervals and interval matrices have been discussed in this chapter.?The chapter作者: 影響深遠 時間: 2025-3-30 07:34 作者: narcissism 時間: 2025-3-30 09:18
Fuzzy Numberssical real numbers and its arithmetic.?There exist different types of fuzzy numbers, but for the sake of completeness of the chapter, triangular, trapezoidal, and Gaussian fuzzy numbers based on the membership functions have only been included here. Further, the conversions of these fuzzy numbers to作者: 廢止 時間: 2025-3-30 15:00 作者: 監(jiān)禁 時間: 2025-3-30 16:50 作者: 名義上 時間: 2025-3-30 21:15
Interval System of Linear Equationsrcuit analysis, robotics, etc. and there exist variety of methods for solving such differential equations.?Generally, under static conditions, the governing differential equations get converted to system of equations. But in actual practice, as a result of errors in measurements, observations, calcu
