Описание: This monograph provides a comprehensive overview of methods for searching, evaluating, and optimizing highway location and alignments using genetic algorithms (GAs), a powerful Artificial Intelligence (AI) technique. It presents a two-level programming structure to deal with the effects of varying highway location on traffic level changes in surrounding road networks within the highway location search and alignment optimization process. In addition, the proposed method evaluates environmental impacts as well as all relevant highway costs associated with its construction, operation, and maintenance. The monograph first covers various search methods, relevant cost functions, constraints, computational efficiency, and solution quality issues arising from optimizing the highway alignment optimization (HAO) problem. It then focuses on applications of a special-purpose GA in the HAO problem where numerous highway alignments are generated and evaluated, and finally the best ones are selected based on costs, traffic impacts, safety, energy, and environmental considerations. A review of other promising optimization methods for the HAO problem is also provided in this monograph.
Автор: Adouane, Lounis Название: Autonomous Vehicle Navigation ISBN: 036757490X ISBN-13(EAN): 9780367574901 Издательство: Taylor&Francis Рейтинг: Цена: 6889.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Robert Istepanian; James F. Whidborne Название: Digital Controller Implementation and Fragility ISBN: 144711082X ISBN-13(EAN): 9781447110828 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written by leading researchers, this book collects a number of articles considering the problems of finite-precision computing in digital controllers and filters. Topics range from analysis of fragility and finite-precision effects to the design of low-complexity digital controllers.
Автор: Uzam, Murat Название: PIC16F1847 Microcontroller-Based Programmable Logic Controller ISBN: 0367506432 ISBN-13(EAN): 9780367506438 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The volume focusses on intermediate concepts of the PIC16F1847-Based PLC project, and covers arithmetical, shift and rotate, selection, demultiplexer (DMUX), decoder, priority encoder and conversion macros, illustrated using flowcharts.
Автор: Uzam, Murat Название: PIC16F1847 Microcontroller-Based Programmable Logic Controller ISBN: 0367506483 ISBN-13(EAN): 9780367506483 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Current volume presents advanced concepts of the PIC16F1847-Based PLC project and consists of topics like program control, high speed counter and PWM macros. It further explains memory related drum sequencer instruction, sequential functional charts, and analog input and output modules.
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: Xin-She Yang; Xing-Shi He Название: Mathematical Foundations of Nature-Inspired Algorithms ISBN: 3030169359 ISBN-13(EAN): 9783030169350 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms.
This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems.
Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications.
Tentative Table of Contents/Topic Coverage:?
- Neural Computation
- Evolutionary Computing Methods
- Neuroscience driven AI Inspired Algorithms
- Biological System based algorithms
- Hybrid and Intelligent Computing Algorithms
- Application of Natural Computing
- Review and State of art analysis of Optimization algorithms
- Molecular and Quantum computing applications
- Swarm Intelligence
- Population based algorithm and other optimizations
