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دسته بندی: کامپیوتر ویرایش: نویسندگان: Patricia Melin, Oscar Castillo, Janusz Kacprzyk سری: Studies in Computational Intelligence, 915 ISBN (شابک) : 3030587274, 9783030587277 ناشر: Springer سال نشر: 2020 تعداد صفحات: 338 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 15 مگابایت
در صورت تبدیل فایل کتاب Recent Advances of Hybrid Intelligent Systems Based on Soft Computing به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب پیشرفت های اخیر سیستم های هوشمند ترکیبی مبتنی بر محاسبات نرم نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
این کتاب پیشرفتهای اخیر در منطق فازی، شبکههای عصبی و
الگوریتمهای بهینهسازی و همچنین ترکیبات ترکیبی آنها و
کاربرد آنها در زمینههایی مانند کنترل هوشمند و رباتیک، تشخیص
الگو، تشخیص پزشکی، پیش بینی سری های زمانی و بهینه سازی مسائل
پیچیده این کتاب شامل مجموعه ای از مقالات متمرکز بر سیستم های
هوشمند ترکیبی مبتنی بر محاسبات نرم است. مقالاتی با موضوع اصلی
منطق فازی نوع 1 و نوع 2 وجود دارد که اساساً شامل مقالاتی است
که مفاهیم و الگوریتم های جدیدی را بر اساس منطق فازی نوع 1 و
نوع 2 و کاربردهای آنها پیشنهاد می کند. همچنین مقالاتی وجود
دارد که تئوری و عمل فراابتکاری را در حوزه های مختلف کاربرد
ارائه می کنند. گروه دیگری از مقالات کاربردهای متنوع منطق
فازی، شبکه های عصبی و سیستم های هوشمند ترکیبی را در کاربردهای
پزشکی توصیف می کنند. همچنین مقالاتی وجود دارد که تئوری و عملی
شبکه های عصبی را در حوزه های مختلف کاربردی ارائه می کنند.
علاوه بر این، مقالاتی وجود دارد که تئوری و عمل بهینهسازی و
الگوریتمهای تکاملی را در حوزههای مختلف کاربردی ارائه
میکنند. در نهایت، مقالاتی وجود دارد که کاربردهای منطق فازی،
شبکههای عصبی و فراابتکاری را در مسائل تشخیص الگو توصیف
میکنند.
This book describes recent advances on fuzzy logic, neural
networks and optimization algorithms, as well as their hybrid
combinations, and their application in areas such as
intelligent control and robotics, pattern recognition,
medical diagnosis, time series prediction and optimization of
complex problems. The book contains a collection of papers
focused on hybrid intelligent systems based on soft
computing. There are some papers with the main theme of
type-1 and type-2 fuzzy logic, which basically consists of
papers that propose new concepts and algorithms based on
type-1 and type-2 fuzzy logic and their applications. There
are also some papers that present theory and practice of
meta-heuristics in different areas of application. Another
group of papers describes diverse applications of fuzzy
logic, neural networks and hybrid intelligent systems in
medical applications. There are also some papers that present
theory and practice of neural networks in different areas of
application. In addition, there are papers that present
theory and practice of optimization and evolutionary
algorithms in different areas of application. Finally, there
are some papers describing applications of fuzzy logic,
neural networks and meta-heuristics in pattern recognition
problems.
Preface Contents Optimization of Fuzzy Logic Controllers with Distributed Bio-Inspired Algorithms 1 Introduction 2 Fuzzy Inference Systems for Control 3 Bioinspired Algorithms 3.1 Genetic Algorithms 3.2 Particle Swarm Optimization 3.3 Other Bioinspired Algorithms 4 Related Work 5 Distributed Bioinspired Algorithms 6 Conclusions References Parallel-Machine Scheduling Problem: An Experimental Study of Instances Difficulty and Algorithms Performance 1 Introduction 2 Approaches for Characterization of Instance Difficulty for COPs 3 The Parallel-Machine Scheduling Problem 3.1 R||Cmax benchmark of instances 3.2 Algorithms for the R||Cmax 4 Experimental Study of the Optimization Process of R||Cmax 4.1 Phase 1: Characterization 4.2 Phase 2: Characteristics Refining 4.3 Phase 3: Study of Relations 4.4 Phase 4: Explanations of the Algorithm Behavior 5 Conclusions and Future Research References Comparison of Genetic Algorithm and Particle Swarm Optimization of Ensemble Neural Networks for Complex Time Series Prediction 1 Introduction 2 Problem Statement and Proposed Method 2.1 Analyze the Time Series 2.2 Creation of the Ensemble Neural Network 2.3 Type-1 and Type-2 Fuzzy System Integration 2.4 GA Applied for the Optimization of the Fuzzy System 2.5 Optimization of the Fuzzy Systems with PSO 3 Simulation Results 3.1 US Dollar/MX Time Series Prediction Based on the GA 3.2 US Dollar/MX Time Series Prediction for the PSO 4 Comparison of Results 4.1 Statistical T Student Test for the Ensemble Neural Network 4.2 The Best Architecture for the Ensemble Neural Network 5 Conclusions References Path Planning by Search Algorithms in Graph-Represented Workspaces 1 Introduction 2 Methodology 2.1 Algorithms Description and Analysis 2.2 Workspace Design 2.3 Experiments 3 Results and Discussion 4 Conclusions and Future Work References Evaluation of Deep Learning Algorithms for Traffic Sign Detection to Implement on Embedded Systems 1 Introduction 2 Background and Motivation 2.1 Deep Learning Method for Traffic Sign Detection 2.2 Traffic Sign Detection Database 2.3 Embedded System 3 Proposed Methodology 3.1 Model Selection 3.2 TSD System 3.3 Embedded System 3.4 Evaluation Metrics 3.5 Training and Evaluation 4 Experiments and Results 4.1 Detection in the LISA Dataset 5 Analysis 6 Conclusions and Future Work References Performance Comparison of Parallel PSO-GA Algorithm with Dynamic Parameter Adjustment Using Type-1 and Interval Type-2 Fuzzy Systems 1 Introduction 2 Particle Swarm Optimization 3 Genetic Algorithms 4 Parallel PSO-GA Algorithm 5 Fuzzy Logic Systems 6 Experiments and Results 7 Conclusions References A Novel Study of the Multi-verse Optimizer and Its Applications on Multiple Areas of Computer Science 1 Introduction 2 Multi-verse Optimizer Algorithm 3 Other Optimization Algorithms 4 Some Applications of MVO 5 Conclusions References Comparative Study of Type-1 and Interval Type-2 Fuzzy Systems in Parameter Adaptation of the Fuzzy Flower Pollination Algorithm 1 Introduction 2 Fuzzy Logic 2.1 The Origins of Fuzzy Logic 2.2 Type-2 Fuzzy Logic Systems 3 Flower Pollination Algorithm 4 Simulation 4.1 Benchmark Functions 4.2 Results 5 Conclusions References A Comparative Study of the Grey Wolf Optimizer and Firefly Algorithm in Mathematical Benchmark Functions of the CEC 15 Competition 1 Introduction 2 Grey Wolf Optimizer Algorithm 3 Firefly Algorithm 4 Simulations Results 5 Conclusions References Optimization of Fuzzy Controllers for Autonomous Mobile Robots Using the Stochastic Fractal Search Method 1 Introduction 2 Stochastic Fractal Search (SFS) 3 Methodology 4 Experimentation and Results 5 Conclusions References Fuzzy Dynamic Parameter Adaptation for Particle Swarm Optimization of Modular Granular Neural Networks Applied to Time Series Prediction 1 Introduction 2 Basic Concepts 2.1 Modular Neural Networks 2.2 Fuzzy Logic 2.3 Granular Computing 2.4 Particle Swarm Optimization 3 Proposed Method 3.1 Modular Granular Neural Networks Applied to Time Series Prediction 3.2 Description of the Fuzzy Dynamic Parameters Adaptation for Particle Swarm Optimization 3.3 Application to Time Series Prediction 3.4 Description of Mackey-Glass Time Series 4 Experimental Results 4.1 Non-optimized Results 4.2 Optimized Results 4.3 Comparison Results 5 Conclusions References Review of Fuzzy Control for Path Tracking in the Robotino System 1 Introduction 2 Kinematic of Robotino 3 Previous Works 4 Analysis of Results 5 Conclusions References Optimization of Routes of a Robot Using Bioinspired Algorithms 1 Introduction 2 Particle Swarm Optimization 3 Ant Colony Optimization 4 Traveling Salesman Problem 5 Type-1 Fuzzy Logic 6 Fuzzy Optimization 7 Simulation Results 8 Conclusions References Optimal Design of Fuzzy Logic Systems Through a Chicken Search Optimization Algorithm Applied to a Benchmark Problem 1 Introduction 2 Related Works 3 Fuzzy Logic System 3.1 Fuzzy Logic Controllers 4 Chicken Search Optimization 5 Study Case 6 Simulations Results 7 Comparative Results 8 Conclusions References Optimization of Fuzzy Trajectory Tracking in Autonomous Mobile Robots Based on Bio-inspired Algorithms 1 Introduction 2 Related Works 3 Basic Concepts of Fuzzy Systems 3.1 Fuzzy Logic System 3.2 Fuzzy Logic Controllers 4 Case Study 5 Bio-inspired Algorithm 5.1 Chicken Search Algorithm 5.2 Bee Colony Optimization 6 Simulation Results 7 Comparative Analysis 8 Statistical Test 9 Conclusions References Swarm Intelligence: A Review of Optimization Algorithms Based on Animal Behavior 1 Introduction 2 Literature Review 2.1 Firefly Algorithm 2.2 Ant Colony Optimization 2.3 Particle Swarm Optimization 2.4 Bee Colony Optimization 2.5 Bat Algorithm 3 Applications 3.1 Firefly Applications 3.2 ACO Applications 3.3 PSO Applications 3.4 BCO Applications 3.5 BA Applications 4 Conclusions References Optimization of Fuzzy Systems Through Metaheuristics in Control Systems 1 Introduction 2 Literature Review 2.1 Differential Evolution Algorithm and Its Origins 2.2 Initial Population 2.3 Strategy 2.4 Fuzzy Logic 2.5 Inverted Pendulum 2.6 Inverted Pendulum Dynamics 3 Methodology 4 Fuzzy Logic Controller 5 Results and Discussion 6 Conclusions and Future Work References Optimal Design of Interval Type-2 Fuzzy Tracking Controllers of Mobile Robots Using a Metaheuristic Algorithm 1 Introduction 2 Shark Smell Optimization (SSO) 2.1 Behavior and Structure of SSO 2.2 Background on SSO 3 Dynamic Setting of Parameters Membership Functions of the Fuzzy Controller with the SSO 3.1 Dynamic Adaptation of Fuzzy Controller Parameters with the Proposed Methodology 3.2 Fuzzy Logic Controller 3.3 Interval Type-2 Fuzzy Logic 4 Study Cases 4.1 Case 1: Benchmark Functions 4.2 Case: Fuzzy Controller of an Autonomous Mobile Robot 5 Simulation Results 5.1 Case 1 Results: Benchmark Functions 5.2 Case 2 Results: Dynamic Adjustment of Fuzzy Controller Parameters 6 Conclusions References