Titlebook: Soft Computing Applications in Optimization, Control, and Recognition; Patricia Melin,Oscar Castillo Book 2013 Springer-Verlag Berlin Heid

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1434-9922 tion of complex problems.Introduces new models and algorithm.Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern

lactic

Type-2 Fuzzy Weight Adjustment for Backpropagation in Prediction Time Series and Pattern Recognitionweight adaptation and especially fuzzy weights. In this work an ensemble neural network of three neural networks and average integration to obtain the final result is presented. The proposed approach is applied to a case of time series prediction and to pattern recognition.

含糊

Book 2013ok describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new

GEST

Optimization of Type-2 and Type-1 Fuzzy Tracking Controllers for an Autonomous Mobile Robot under Peions is applied to solve this motion problem by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application.

地牢

A Genetic Algorithm for the Problem of Minimal Brauer Chains for Large Exponentsentiation can significantly improve the execution time of cryptosystems. The problem of determining the minimal sequence of multiplications required for performing a modular exponentiation can be formulated using the concept of Brauer Chains..This paper, shows a new approach to face the problem of g

异端邪说2

Cellular Processing Algorithmsre the search process. In this work we propose a cellular processing approach to solve optimization problems. The main components of these algorithms are: the processing cells (PCells), the communication between PCells, and the global and local stagnation detection. The great flexibility and simplic

AMOR

parsimony

Particle Swarm Optimization for Multi-objective Control Design Using AT2-FLC in FPGA Devicen Interval of Type-2 Fuzzy Logic Controller (AT2-FLC) using bio-inspired algorithms, such as Particle Swarm Optimization (PSO). The optimization only considers certain points of the membership functions, the fuzzy rules are not modified, so that the algorithm minimizes the runtime. Based on the conc

擦掉

Genetic Optimization of Modular Type-1 Fuzzy Controllers for Complex Control Problemsquires five individual controllers. Simulation results with a genetic algorithm for optimizing the membership functions of the five individual controllers are presented. Simulation results show that the proposed modular control approach offers advantages over existing control methods.