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This book explores the transformative potential of machine learning (ML) technologies in agriculture. It delves into specific applications, such as crop monitoring, disease detection, and livestock management, demonstrating how artificial intelligence/machine learning (AI/ML) can optimize resource management and improve overall productivity in farming practices. Sustainable Farming through Machine Learning: Enhancing Productivity and Efficiency provides an in-depth overview of AI and ML concepts relevant to the agricultural industry. It discusses the challenges faced by the agricultural sector and how AI/ML can address them. The authors highlight the use of AI/ML algorithms for plant disease...
This book enables the readers to design, optimize, and control complex systems with greater precision and efficiency. It further provides practical insights and presents case studies for readers interested in exploring the intersections between artificial intelligence and industry. This book discusses important topics such as algorithmic design, mathematical modeling, natural language processing, machine learning, and computer vision. This book: Explores practical applications of artificial intelligence in engineering, including optimization, predictive modeling, decision‐making, and control systems Provides real‐world examples of the applications of artificial intelligence in engineerin...
The need for tailored data for machine learning models is often unsatisfied, as it is considered too much of a risk in the real-world context. Synthetic data, an algorithmically birthed counterpart to operational data, is the linchpin for overcoming constraints associated with sensitive or regulated information. In high-dimensional data, where the dimensions of features and variables often surpass the number of available observations, the emergence of synthetic data heralds a transformation. Applications of Synthetic High Dimensional Data delves into the algorithms and applications underpinning the creation of synthetic data, which surpass the capabilities of authentic datasets in many cases...
Inspired by the community behaviors of animals and humans, cooperative control has been intensively studied by numerous researchers in recent years. Cooperative control aims to build a network system collectively driven by a global objective function in a distributed or centralized communication network and shows great application potential in a wide domain. From the perspective of cybernetics in network system cooperation, one of the main tasks is to design the formation control scheme for multiple intelligent unmanned systems, facilitating the achievements of hazardous missions – e.g., deep space exploration, cooperative military operation, and collaborative transportation. Various chall...
On NilĐakanĐtĐha Dasa, 1884-1967, legislator in the Central Legislative Assembly, 1924-1930 and 1935-1945, in the Orissa Legislative Assembly, 1952-1961.
The volume contains original research papers as the Proceedings of the International Conference on Applied Nonlinear Analysis and Soft Computing (ANASC 2020), held at Gauhati University, Guwahati, India, on 22-23 December, 2020. It focuses on current research topics in applied analysis including nonlinearity, soft computing and related areas. It primarily includes topics related to pattern recognition, reaction-diffusion problem, decision making problems, inventory model, predator-prey model, logistic models, wave problems, problems in Magnetohydrodynamics, cosmological model, harmonic functions, graphs, shapes, etc. Researchers, educators, scientist and professionals interested in recent developments in applied analysis including nonlinearity aspects and soft computing should be benefited from this volume.
This book presents high-quality papers from the Fourth International Conference on Microelectronics, Computing & Communication Systems (MCCS 2019). It discusses the latest technological trends and advances in MEMS and nanoelectronics, wireless communication, optical communication, instrumentation, signal processing, image processing, bioengineering, green energy, hybrid vehicles, environmental science, weather forecasting, cloud computing, renewable energy, RFID, CMOS sensors, actuators, transducers, telemetry systems, embedded systems and sensor network applications. It includes papers based on original theoretical, practical and experimental simulations, development, applications, measurements and testing. The applications and solutions discussed here provide excellent reference material for future product development.
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This book includes selected papers from the 2nd International Conference on Machine Learning and Information Processing (ICMLIP 2020), held at Vardhaman College of Engineering, Jawaharlal Nehru Technological University (JNTU), Hyderabad, India, from November 28 to 29, 2020. It presents the latest developments and technical solutions in the areas of advanced computing and data sciences, covering machine learning, artificial intelligence, human–computer interaction, IoT, deep learning, image processing and pattern recognition, and signal and speech processing.