دسترسی نامحدود
برای کاربرانی که ثبت نام کرده اند
برای ارتباط با ما می توانید از طریق شماره موبایل زیر از طریق تماس و پیامک با ما در ارتباط باشید
در صورت عدم پاسخ گویی از طریق پیامک با پشتیبان در ارتباط باشید
برای کاربرانی که ثبت نام کرده اند
درصورت عدم همخوانی توضیحات با کتاب
از ساعت 7 صبح تا 10 شب
دسته بندی: برنامه نويسي ویرایش: نویسندگان: Information Resources Management Association سری: ISBN (شابک) : 9781799880998, 1799880990 ناشر: IGI Global سال نشر: 2021 تعداد صفحات: 1569 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 102 مگابایت
در صورت تبدیل فایل کتاب Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms 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 گلچین تحقیق در مورد کاربردهای چند صنعت از برنامه نویسی ژنتیک و الگوریتم ها 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.
برنامه نویسی ژنتیکی یک روش جدید و تکاملی است که به یک حوزه جدید تحقیقاتی در هوش مصنوعی تبدیل شده است که به دلیل تولید خودکار راه حل های با کیفیت بالا برای مسائل بهینه سازی و جستجو شناخته شده است. این جنبه خودکار از الگوریتمها و تقلید از انتخاب طبیعی و ژنتیک، برنامهریزی ژنتیکی را به یک مؤلفه هوشمند در حل مسئله تبدیل میکند که به دلیل کارایی و قابلیتهای وسیع آن بسیار مورد توجه قرار میگیرد. الگوریتم های ژنتیک و برنامه نویسی با قابلیت اصلاح و تطبیق، توزیع آسان و موثر در مقیاس بزرگ/گسترده مسائل، می توانند در بسیاری از صنایع مختلف مورد استفاده قرار گیرند. کاربردهای این چند صنعت از امور مالی و اقتصادی گرفته تا تجارت و مدیریت و مراقبت های بهداشتی و علوم متفاوت است. استفاده از برنامه نویسی و الگوریتم های ژنتیکی فراتر از توانایی های انسان است، تجارت و فرآیندهای صنایع مختلف ضروری را بهبود می بخشد و عملکرد را در طول مسیر بهبود می بخشد. مجموعه تحقیقاتی در مورد کاربردهای چند صنعتی برنامهریزی ژنتیک و الگوریتمها، پیادهسازی، ابزارها و فنآوریها و تأثیری که برنامهنویسی و الگوریتمهای ژنتیک در صنایع مختلف داشتهاند را بر جامعه پوشش میدهد. این کتاب با در نظر گرفتن یک رویکرد چند صنعت، مبانی برنامهنویسی ژنتیک را از طریق مزایا و چالشهای فنآوری آن همراه با آخرین پیشرفتها و چشماندازهای آینده برای علوم کامپیوتر پوشش میدهد. این کتاب برای دانشگاهیان، مهندسان زیست شناسی، برنامه نویسان کامپیوتر، دانشمندان، محققان و دانشجویان سطح بالایی که به دنبال آخرین تحقیقات در مورد برنامه ریزی ژنتیکی هستند، ایده آل است.
Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.
Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms List of Contributors Table of Contents Preface Section 1: Fundamental Concepts and Theories 1 Mathematical Optimization by Using Particle Swarm Optimization, Genetic Algorithm, and Differential Evolution and Its Similarities 2 Missing Value Imputation Using ANN Optimized by Genetic Algorithm 3 A Unified Feature Selection Model for High Dimensional Clinical Data Using Mutated Binary Particle Swarm Optimization and Genetic Algorithm 4 PID Control Algorithm Based on Genetic Algorithm and its Application in Electric Cylinder Control 5 Portfolio Optimization and Asset Allocation With Metaheuristics: A Review Section 2: Development and Design Methodologies 6 Determination of Spatial Variability of Rock Depth of Chennai 7 Optimization of Windspeed Prediction Using an Artificial Neural Network Compared With a Genetic Programming Model 8 A Novel Hybrid Genetic Algorithm for Unconstrained and Constrained Function Optimization 9 An Improved Genetic Algorithm for Document Clustering on the Cloud 10 Research on an Improved Coordinating Method Based on Genetic Algorithms and Particle Swarm Optimization 11 A Hybrid Approach for Shape Retrieval Using Genetic Algorithms and Approximate Distance 12 Innovative Genetic Algorithmic Approach to Select Potential Patches Enclosing Real and Complex Zeros of Nonlinear Equation 13 Neuronal Communication Genetic Algorithm-Based Inductive Learning 14 Genetic Algorithm With Hill Climbing for Correspondences Discovery in Ontology Mapping 15 Cross-Project Change Prediction Using Meta-Heuristic Techniques 16 Environmental Adaption Method: A Heuristic Approach for Optimization 17 Decision Choice Optimization With Genetic Algorithm in Communication Networks 18 Optimal Designs by Means of Genetic Algorithms 19 T-Spanner Problem: Genetic Algorithms for the T-Spanner Problem 20 An Improved Genetic Algorithm for Solving Multi Depot Vehicle Routing Problems 21 A Modified Kruskal’s Algorithm to Improve Genetic Search for Open Vehicle Routing Problem Section 3: Tools and Technologies 22 Gene Expression Programming 23 Genetic-Fuzzy Programming Based Linkage Rule Miner (GFPLR-Miner) for Entity Linking in Semantic Web 24 Implement Multichannel Fractional Sample Rate Convertor using Genetic Algorithm 25 A Genetic-Algorithms-Based Technique for Detecting Distributed Predicates 26 A Multi-Objective Approach fo rMaterialized View Selection 27 Tracking Patterns with Particle Swarm Optimization and Genetic Algorithms 28 Exploration of Fuzzy System With Applications 29 Best Feature Selection for Horizontally Distributed Private Biomedical Data Based on Genetic Algorithms 30 Intelligent Computing in Medical Imaging: A Study 31 Optimization Techniques Applications in Biochemical Engineering and Controlled Drug Delivery: Current Practices andForthcoming Challenges 32 Application of Computational Intelligence in Network Intrusion Detection: A Review 33 Determining Headache Diseases With Genetic Algorithm 34 Web Page Recommender System using hybrid of Genetic Algorithm and Trust for Personalized Web Search 35 A Multiobjective Genetic-Algorithm-Based Optimization of Micro-Electrical Discharge Drilling: Enhanced Quality Micro-Hole Fabrication in Inconel 718 Section 4: Utilization and Applications 36 Application of Natural-Inspired Paradigms on System Identification: Exploring the Multivariable Linear Time Variant Case 37 Variable Selection Method for Regression Models Using Computational Intelligence Techniques 38 Delay Optimization Using Genetic Algorithm at the Road Intersection 39 Energy and SLA Efficient Virtual Machine Placement in Cloud Environment Using Non-Dominated Sorting Genetic Algorithm 40 The Genetic Algorithm: An Application on Portfolio Optimization 41 DNA Fragment Assembly Using Quantum-Inspired Genetic Algorithm 42 Genetic Algorithm-Influenced Top-N Recommender System to Alleviate the NewUser Cold Start Problem 43 GA-Based OptimizedImage Watermarking Method With Histogram and Butterworth Filtering 44 Performance Analysis of Nature-Inspired Algorithms-Based Bayesian Prediction Models for Medical Data Sets 45 Medical Image Thresholding Using Genetic Algorithm and Fuzzy Membership Functions: A Comparative Study 46 Analysis and Comparison of Clustering Techniques for Chronic Kidney Disease With Genetic Algorithm 47 An Efficient Batch Scheduling Model for Hospital Sterilization Services Using Genetic Algorithm 48 Implementing Genetic Algorithms to Assist Oil and Gas Pipeline Integrity Assessment and Intelligent Risk Optimization Section 5: Organizational and Social Implications 49 A Secured Predictive Analytics Using Genetic Algorithm and Evolution Strategies 50 Optimization and Evolution in Architectural Morphogenesis: Evolutionary Principles Applied to Mass Housing 51 Home Load-Side Management in Smart Grids Using Global Optimization 52 A Novel Approach for Business Process Model Matching Using Genetic Algorithms 53 Performance Evaluation of Population Seeding Techniques of Permutation-Coded GA Traveling Salesman Problems Based Assessment: Performance Evaluation of Population Seeding Techniques of Permutation-Coded GA 54 Real Time Scheduling Optimization 55 New Hybrid Genetic Based Approach for Real-Time Scheduling of Reconfigurable Embedded Systems 56 Solving Flow Shop Scheduling Problems with Blocking byusing Genetic Algor 57 Genetic Algorithm Approach for Inventory and Supply Chain Management: A Review 58 A Decision-Making Tool for the Optimization of Empty Containers’ Return in the Liner Shipping: Optimization by Using the Genetic Algorithm 59 Solving Nurse Scheduling Problem via Genetic Algorithm in Home Healthcare 60 Use SUMO Simulator for the Determination of Light Times in Order to Reduce Pollution: A Case Study in the City Center of Rio Grande, Brazil 61 A Rule Based Classification for Vegetable Production Using Rough Set and Genetic Algorithm Section 6: Critical Issues and Challenges 62 A Survey on Grey Optimization 63 Genetic-Algorithm-Based Performance Optimization for Non-Linear MIMO System 64 Privacy Preserving Feature Selection for Vertically Distributed Medical Data Based on Genetic Algorithms and Naïve Bayes 65 Applying the Computational Intelligence Paradigm to Nuclear Power Plant Operation: A Review (1990-2015) 66 The Study of Genetic Type Steganographic Models to Increase Noise Immunity of IoT Systems Section 7: Emerging Trends 67 An Improved Genetic Algorithm and A New Discrete Cuckoo Algorithm for Solving the Classical Substitution Cipher 68 Performance Evaluation of VM Placement Using Classical Bin Packing and Genetic Algorithm for Cloud Environment 70 Genetic Algorithm Influenced Top-N Recommender System to Alleviate New User Cold Start Problem 71 A Hybrid Tabu Genetic Metaheuristic for Selection of Security Controls Index 69 A Controlled Stability Genetic Algorithm With the New BLF2G Guillotine Placement Heuristic for the Orthogonal Cutting-Stock Problem