Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations.
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Particle Swarm Optimization Based Noncoherent Detector for Ultra-Wideband Radio in Intensive Multipath Environments
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: IResearch Article Suboptimal Partial Transmit Sequence-Active Interference Cancellation with Particle Swarm Optimization
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Ultra-Wideband Source Localization Using a Particle-Swarm-Optimized Capon Estimator from a Frequency-Dependent Channel Modeling Viewpoint
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Particle Swarm Optimization for Adaptive Resource Allocation in Communication Networks
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Suboptimal PTS Algorithm Based on Particle Swarm Optimization Technique for PAPR Reduction in OFDM Systems
Recently, there is a growing interest in working with tree-structured data in different applications and domains such as computational biology and natural language processing. Moreover, many applications in computational linguistics require the computation of similarities over pair of syntactic or semantic trees. In this context, Tree Edit Distance (TED) has been widely used for many years. However, one of the main constraints of this method is to tune the cost of edit operations, which makes it difﬁcult or sometimes very challenging in dealing with complex problems. ...
In the era globalisation the emerging technologies are governing engineering industries to a
multifaceted state. The escalating complexity has demanded researchers to find the possible
ways of easing the solution of the problems. This has motivated the researchers to grasp
ideas from the nature and implant it in the engineering sciences.
Heuristic Search is an important sub-discipline of optimization theory and finds applications in a vast variety of fields, including life science and engineering. Search methods have been useful in solving tough engineering-oriented problems that either could not be solved any other way or solutions take a very long time to be computed. This book explores a variety of applications for search methods and techniques in different fields of electrical engineering.
The book consists of 29 chapters. Chapters 1 to 9 describe the algorithms for enhancing
the search performance of evolutionary algorithms such as Genetic Algorithm, Swarm
Optimization Algorithm and Quantum-inspired Algorithm. Chapter 10 introduces the
programming language for evolutionary algorithm. Chapter 11 explains evolutionary
algorithms for the fuzzy data problems. Chapters 12 to 13 discuss theoretical analysis
of evolutionary algorithms. The remaining chapters describe the applications of the evolutionary algorithms. ...
This book presents several recent advances on Evolutionary Computation, specially
evolution-based optimization methods and hybrid algorithms for several applications, from
optimization and learning to pattern recognition and bioinformatics. Concerning evolutionbased
optimization methods, this book presents diverse versions of genetic algorithms,
genetic programming, and performance studies and analyses, as well as several particle
swarm optimizers and hybrid approaches using neural networks and artificial
immunological systems for multi-objective optimization....
The Handbook of Bioinspired Algorithms and Applications seeks to provide an opportunity for researchers
to explore the connection between biologically inspired (or bioinspired) techniques and the development
of solutions to problems that arise in a variety of problem domains. The power of bioinspired paradigms
lies in their capability in dealingwith complex problemswith little or no knowledge about the search space,
and thus is particularly well suited to deal with a wide range of computationally intractable optimizations
and decision-making applications....
Volume flow rate of compressed air is provided by a separate rate
Pneumatic valve for each engine.
This article is structured as follows: first, a mathematical modeling of mechatronic systems
origin, which results in a state-space description of nonlinear icon.
Motivated by the need of energy-efficiency improvements, process optimization, soft-start capability and numerous other environmental benefits, it may be desirable to operate induction motors for many applications at continuously adjustable speeds. The induction motor drives can provide high productivity with energy efficiency in different industrial applications and are the basis for modern automation. This book provides an account of this developing subject through such topics as modelling, noise, control techniques used for high-performance applications and diagnostics....
The typical method used in training and testing
assessment conducted in this task will be considered and are as follows. Training in object recognition is often related to the training of an experiment. In the case of
object recognition memory, as a measure to declare memory, acquisition is said to occur less exposure to the stimulus is learning / more acceptable in the absence of
declared memory (eg a procedure for memory skills). Training in object recognition
task involves exposing rodents second stimulus....