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Handbook of Research on Smart Technology Models for Business and Industry
Advances in machine learning techniques and ever-increasing computing power has helped create a new generation of hardware and software technologies with practical applications for nearly every industry. As the progress has, in turn, excited the interest of venture investors, technology firms, and a growing number of clients, implementing intelligent automation in both physical and information systems has become a must in business. Handbook of Research on Smart Technology Models for Business and Industry is an essential reference source that discusses relevant abstract frameworks and the latest experimental research findings in theory, mathematical models, software applications, and prototypes in the area of smart technologies. Featuring research on topics such as digital security, renewable energy, and intelligence management, this book is ideally designed for machine learning specialists, industrial experts, data scientists, researchers, academicians, students, and business professionals seeking coverage on current smart technology models.
Handbook of Research on Smart Computing for Renewable Energy and Agro-Engineering
The rise in population and the concurrently growing consumption rate necessitates the evolution of agriculture to adopt current computational technologies to increase production at a faster and smoother scale. While existing technologies may help in crop processing, there is a need for studies that seek to understand how modern approaches like artificial intelligence, fuzzy logic, and hybrid algorithms can aid the agricultural process while utilizing energy sources efficiently. The Handbook of Research on Smart Computing for Renewable Energy and Agro-Engineering is an essential publication that examines the benefits and barriers of implementing computational models to agricultural production and energy sources as well as how these models can produce more cost-effective and sustainable solutions. Featuring coverage on a wide range of topics such as bacterial foraging, swarm intelligence, and combinatorial optimization, this book is ideally designed for agricultural engineers, farmers, municipal union leaders, computer scientists, information technologists, sustainable developers, managers, environmentalists, industry professionals, academicians, researchers, and students.
Intelligent Computing & Optimization
This book includes innovative research work presented at ICO’2018, the 1st International Conference on Intelligent Computing and Optimization, held in Pattaya, Thailand on October 4–5, 2018. The conference presented topics ranging from power quality, reliability, security assurance, cloud computing, smart cities, renewable energy, agro-engineering, smart vehicles, deep learning, block chain, power systems, AI, machine learning, manufacturing systems, and big-data analytics. This volume focuses on subjects related to innovative computing, uncertainty management and optimization approaches to real-world problems in big-data, smart cities, sustainability, meta-heuristics, cyber-security, Io...
Applications of Artificial Neural Networks for Nonlinear Data
Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.
Deep Learning Techniques and Optimization Strategies in Big Data Analytics
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.
Advances in Soft Computing
This volume constitutes the proceedings of the 18th Mexican Conference on Artificial Intelligence, MICAI 2019, held in Xalapa, Mexico, in October/November 2019. The 59 full papers presented in this volume were carefully reviewed and selected from 148 submissions. They cover topics such as: machine learning; optimization and planning; fuzzy systems, reasoning and intelligent applications; and vision and robotics.
Handbook of Research on Energy-Saving Technologies for Environmentally-Friendly Agricultural Development
World population growth and the related increase in the demand for food and other goods has intensified agricultural production throughout the world. Some of today's technologies are characterized by relatively low productivity and high consumption of energy resources. The Handbook of Research on Energy-Saving Technologies for Environmentally-Friendly Agricultural Development is a comprehensive research publication that provides insight into new technologies that create efficient and environmentally-friendly energy potential sufficient for the organization of industrial and social-economic activity in rural areas. Highlighting a variety of topics such as economic development, renewable energy, and climate change, this book is ideal for agricultural business executives, engineers, scientists, environmentalists, entrepreneurs, academicians, researchers, students, and those working in the agro-industrial and housing and communal services sectors.
Human Agro-Energy Optimization for Business and Industry
In the current era, there are many environmental and energy challenges facing the agricultural sector, which negatively impact the climate, business, industry, and society. Through modern technologies and engineering, however, these challenges are now able to be met with solutions. There is a need for research in this area so that the industry can continue to be sustainable. Human Agro-Energy Optimization for Business and Industry presents research on humanized optimization approaches for smart energy and the agro-business industry. It is a critical scholarly resource that examines the efficient use of modern smart farming and renewable energy sources, which have a positive impact on sustainable development. Covering topics such as biomass characterization, energy efficiency, and sustainable development, this premier reference source is an essential resource for agricultural scientists, engineers, government officials, software developers, managers, business leaders, executive officers, students and educators of higher education, librarians, researchers, and academicians.
Analyzing Future Applications of AI, Sensors, and Robotics in Society
The rise of artificial intelligence and its countless branches have caused many professional industries to rethink their traditional methods of practice and develop new techniques to keep pace with technological advancement. The continued use of intelligent technologies in the professional world has propelled researchers to contemplate future opportunities and challenges that artificial intelligence may withhold. Significant research is a necessity for understanding future trends of artificial intelligence and the preparation of prospective issues. Analyzing Future Applications of AI, Sensors, and Robotics in Society provides emerging research exploring the potential uses and future challenges of intelligent technological advancements and their impact in education, finance, politics, business, healthcare, and engineering. Featuring coverage on a broad range of topics such as neuronal networks, cognitive computing, and e-health, this book is ideally designed for practitioners, researchers, scientists, executives, strategists, policymakers, academicians, government officials, developers, and students seeking current research on future societal uses of intelligent technology.
Intelligent Computing and Optimization
This book presents the outcomes of the second edition of the International Conference on Intelligent Computing and Optimization (ICO) – ICO 2019, which took place on October 3–4, 2019, in Koh Samui, Thailand. Bringing together research scholars, experts, and investigators from around the globe, the conference provided a platform to share novel research findings, recent advances and innovative applications in the field. Discussing the need for smart disciplinary processes embedded into interdisciplinary collaborations in the context of meeting the growing global populations’ requirements, such as food and health care, the book highlights the role of intelligent computation and optimization as key technologies in decision-making processes and in providing cutting edge solutions to real-world problems.
