Application Of Nature Based Algorithm In Natural Resource Management
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| Author | : Mrinmoy Majumder |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 348 |
| Release | : 2013-05-23 |
| Genre | : Science |
| ISBN | : 9400751524 |
This book highlights the application of nature-based algorithms in natural resource management. The book includes the methodologies to apply what natural flora or fauna do to optimize their survival. The same technique was used to optimize renewable energy generation from water resources, maximization of profit from crop harvesting, forest resource management and decision-making studies. These studies can be used as an example for finding solutions of the other maximization or minimization problems which are common in natural resource management.
| Author | : Aditya Khamparia |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 201 |
| Release | : 2021-02-08 |
| Genre | : Computers |
| ISBN | : 311067615X |
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
| Author | : Thomas, J. Joshua |
| Publisher | : IGI Global |
| Total Pages | : 355 |
| Release | : 2019-11-29 |
| Genre | : Computers |
| ISBN | : 1799811948 |
Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
| Author | : Srikanta Patnaik |
| Publisher | : Springer |
| Total Pages | : 506 |
| Release | : 2017-03-07 |
| Genre | : Technology & Engineering |
| ISBN | : 3319509209 |
The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.
| Author | : S. Balamurugan |
| Publisher | : John Wiley & Sons |
| Total Pages | : 388 |
| Release | : 2021-12-14 |
| Genre | : Computers |
| ISBN | : 111968174X |
NATURE-INSPIRED ALGORITHMS AND APPLICATIONS The book’s unified approach of balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Inspired by the world around them, researchers are gathering information that can be developed for use in areas where certain practical applications of nature-inspired computation and machine learning can be applied. This book is designed to enhance the reader’s understanding of this process by portraying certain practical applications of nature-inspired algorithms (NIAs) specifically designed to solve complex real-world problems in data analytics and pattern recognition by means of domain-specific solutions. Since various NIAs and their multidisciplinary applications in the mechanical engineering and electrical engineering sectors; and in machine learning, image processing, data mining, and wireless networks are dealt with in detail in this book, it can act as a handy reference guide. Among the subjects of the 12 chapters are: A novel method based on TRIZ to map real-world problems to nature problems Applications of cuckoo search algorithm for optimization problems Performance analysis of nature-inspired algorithms in breast cancer diagnosis Nature-inspired computation in data mining Hybrid bat-genetic algorithm–based novel optimal wavelet filter for compression of image data Efficiency of finding best solutions through ant colony optimization techniques Applications of hybridized algorithms and novel algorithms in the field of machine learning. Audience: Researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks will find this book very useful.
| Author | : H S Madhusudhan |
| Publisher | : CRC Press |
| Total Pages | : 263 |
| Release | : 2024-09-11 |
| Genre | : Computers |
| ISBN | : 1040112641 |
This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of machine learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques. Focuses on virtual machine placement and migration techniques for cloud data centers Presents the role of machine learning and metaheuristic approaches for optimisation in cloud computing services Includes application of placement techniques for quality of service, performance, and reliability improvement Explores data center resource management, load balancing and orchestration using machine learning techniques Analyses dynamic and scalable resource scheduling with a focus on resource management The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology.
| Author | : Chander Kumar Singh |
| Publisher | : CRC Press |
| Total Pages | : 309 |
| Release | : 2018-03-29 |
| Genre | : Nature |
| ISBN | : 1351858424 |
Shelving Guide: This book will present new research regarding the interdisciplinary applications of spatial information sciences for identification, assessment, monitoring, and modeling issues related to natural resources and environmental management. It will focus on the creation, collection, storage, processing, modeling, interpretation, display and dissemination of spatio-temporal data, which could greatly aid with environmental management issues including ecosystem change, resource utilization, land use management, and environmental pollution. The positive environmental impacts of information technology advancements with regard to global environmental and climate change will also be discussed. Features Explains how geospatial information can best serve environmental management needs, including ecosystem change, resource utilization, land use management, and environmental pollution. Examines the environmental impacts of information technology advancements with regard to global environmental and climate change. Focuses on the creation, collection, storage, processing, modeling, interpretation, display and dissemination of environmental spatio-temporal data. Presents examples of applications for spatial information sciences regarding the assessment, monitoring, and modeling of natural resources. Includes practical case studies in every chapter.
| Author | : Dash, Sujata |
| Publisher | : IGI Global |
| Total Pages | : 567 |
| Release | : 2017-08-10 |
| Genre | : Computers |
| ISBN | : 152252858X |
The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.
| Author | : Management Association, Information Resources |
| Publisher | : IGI Global |
| Total Pages | : 1810 |
| Release | : 2016-07-26 |
| Genre | : Computers |
| ISBN | : 1522507892 |
As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.
| Author | : Aditya Khamparia |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 168 |
| Release | : 2021-02-08 |
| Genre | : Computers |
| ISBN | : 3110676117 |
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
