In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.
The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.
The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for ?=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.
The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.
This book focuses on the fields of fuzzy logic and metaheuristic algorithms, particularly the harmony search algorithm and fuzzy control. There are currently several types of metaheuristics used to solve a range of real-world of problems, and these metaheuristics contain parameters that are usually fixed throughout the iterations. However, a number of techniques are also available that dynamically adjust the parameters of an algorithm, such as probabilistic fuzzy logic.
This book proposes a method of addressing the problem of parameter adaptation in the original harmony search algorithm using type-1, interval type-2 and generalized type-2 fuzzy logic. The authors applied this methodology to the resolution of problems of classical benchmark mathematical functions, CEC 2015, CEC2017 functions and to the optimization of various fuzzy logic control cases, and tested the method using six benchmark control problems - four of the Mamdani type: the problem of filling a water tank, the problem of controlling the temperature of a shower, the problem of controlling the trajectory of an autonomous mobile robot and the problem of controlling the speed of an engine; and two of the Sugeno type: the problem of controlling the balance of a bar and ball, and the problem of controlling control the balance of an inverted pendulum. When the interval type-2 fuzzy logic system is used to model the behavior of the systems, the results show better stabilization because the uncertainty analysis is better. As such, the authors conclude that the proposed method, based on fuzzy systems, fuzzy controllers and the harmony search optimization algorithm, improves the behavior of complex control plants.
Автор: Frumen Olivas; Fevrier Valdez; Oscar Castillo; Pat Название: Dynamic Parameter Adaptation for Meta-Heuristic Optimization Algorithms Through Type-2 Fuzzy Logic ISBN: 3319708503 ISBN-13(EAN): 9783319708508 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduction.- Theory and Background.- Problems Statement.- Methodology.- Simulation Results.- Statistical Analysis and Comparison of Results.
Автор: Broussard Corey M. Название: New Tracking Filter Algorithm Using Input Parameter Estimation ISBN: 1288404875 ISBN-13(EAN): 9781288404872 Издательство: Неизвестно Рейтинг: Цена: 56610.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: White Andrew P Название: Linear Parameter-varying Control for Engineering Application ISBN: 1447150392 ISBN-13(EAN): 9781447150398 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The subject of this brief is the application of linear parameter-varying (LPV) control to a class of dynamic systems to provide a systematic synthesis of gain-scheduling controllers with guaranteed stability and performance.
Автор: Amezcua Название: New Classification Method Based on Modular Neural Networks with the LVQ Algorithm and Type-2 Fuzzy Logic ISBN: 3319737724 ISBN-13(EAN): 9783319737720 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this book a new model for data classification was developed. Some architectures were developed in order to work mainly with two datasets, an arrhythmia dataset (using ECG signals) for classifying 15 different types of arrhythmias, and a satellite images segments dataset used for classifying six different types of soil.
Автор: Guha Dipayan, Roy Provas Kumar, Banerjee Subrata Название: Application of Intelligent Control Algorithms to Study the Dynamics of Hybrid Power System ISBN: 981190443X ISBN-13(EAN): 9789811904431 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: With the growing consciousness of global warming and the fast depletion of natural power generation resources, the existing power system is on the verge of transitions to a "hybrid power system (HPS)" integrated with distributed energy resources.
Автор: Leticia Amador; Oscar Castillo Название: Optimization of Type-2 Fuzzy Controllers Using the Bee Colony Algorithm ISBN: 331954294X ISBN-13(EAN): 9783319542942 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: For this reason we consider in this book the proposed method using fuzzy systems, fuzzy controllers, and bee colony optimization algorithm improve the behavior of the complex control problems.
Автор: Dirik Mahmut, Castillo Oscar, Kocamaz Fatih Название: Vision-Based Mobile Robot Control and Path Planning Algorithms in Obstacle Environments Using Type-2 Fuzzy Logic ISBN: 3030692493 ISBN-13(EAN): 9783030692490 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book includes topics, such as: path planning, avoiding obstacles, following the path, go-to-goal control, localization, and visual-based motion control. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and Gaussian Control have been used in overall system design.
Автор: Dirik Mahmut, Castillo Oscar, Kocamaz Fatih Название: Vision-Based Mobile Robot Control and Path Planning Algorithms in Obstacle Environments Using Type-2 Fuzzy Logic ISBN: 3030692469 ISBN-13(EAN): 9783030692469 Издательство: Springer Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book includes topics, such as: path planning, avoiding obstacles, following the path, go-to-goal control, localization, and visual-based motion control. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and Gaussian Control have been used in overall system design.
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