AAP Research Notes on Optimization and Decision Making Theories - Böcker

Multi-criteria decision-making (MCDM) has gained vast popularity for its ability to help make decisions in the presence of various similar and conflicting choices.This new volume applies the MCDM theory to solving problems and challenges in manufacturing environments. It discusses using MCDM computational methods to evaluate and select the most optimal solution or method for real-world, real-time manufacutring engineering issues. It details the decision-making process in relation materials selection; identification, assessment, and evaluation of risk; sustainability assessment; selection of green suppliers; and more.The chapter authors demonstrate the application of myriad MCDM techniques in decision-making, including MADM (multiple attribute decision-making), DEA (data envelopment analysis), fuzzy TOPSIS (technique for order preference by similarities to ideal solution), fuzzy-VIKOR (multicriteria optimization and compromise solution); MOORA (multi-objective optimization on the basis of ratio analysis), EWM (entropy weight method), (AHP) analytic hierarchy process, TODIM (TOmada de Decisao Interativa Multicriterio), and others. The volume illustrates these MCDM models in several industries and industrial processes, including for experimental analysis and optimization of drilling of glass fiber reinforced plastic, in the textile industries, for selection of refrigerants for domestic applications, and others.

This new book delves into how modern technologies—i.e., global positioning systems (GPS), unmanned aerial vehicles (drones), image processing methods, artificial intelligence, machine learning, and deep learning—are being used to make agriculture more farmer-friendly and more economically profitable. The volume focuses on the use of smart sensors, actuators, and decision support systems to provide intelligent data about crop health and for monitoring for yield prediction, soil quality, nutrition requirement prediction, etc. The authors discuss robotic-based innovations in agriculture, soft computing methodologies for crop forecasting, machine learning techniques to classify and identify plant diseases, deep convolutional neural networks for recognizing nutrient deficiencies, and more.

Multimedia security has become one of the most important topics for organizations and individuals. Presenting important state-of-the art multimedia security techniques and algorithms, this book focuses on data encryption, steganography, watermarking, authentication, data hiding, biometric template security, quantum-based video cryptosystems, pan sharpening, and digital signatures to help in protecting the unauthorized access/alteration of multimedia over the Internet and cloud. It also covers the application of machine learning, blockchain, and AI-based methods for multimedia security. Mathematical models used in data hiding and data evaluation techniques are discussed thoroughly to provide a good understanding of the principles of multimedia security.

Modeling, simulation, and optimization are three critical components of modern design practice that have grown tremendously over the last few decades with the increased use of computer-aided designs in engineering and industry. This book takes a multidisciplinary approach to the trends and challenges of computational modeling, simulation, and optimization techniques and their applications in the field of engineering sciences. It presents practical case studies and illustrations of computational techniques on materials and manufacturing in a diverse selection of applications, such as for drug delivery systems, for refrigeration models, for polymer and aluminum metal matrix composites, for automotive and aircraft applications, and even for talent management strategies on retaining talented employees.

Cyber attacks, both on national infrastructures and private companies, have ramped up exponentially in recent years. AI tools and algorithms can help detect and fend off cyber threats, but they can also be used by hackers in their cyber attacks. Defensive measures to address cyber attacks are not sufficient for artificial intelligence-based architectures, which present a new range of challenges. This new volume takes these concerns into consideration and examines recent developments and issues in attacks that target AI based systems and cyber infrastructures while also presenting research on using AI technologies to prevent attacks.

This new volume covers a diverse range of advances in intelligent systems that involve applications of AI and digital automation, such as machine learning, deep learning, sectional convolutional neural network models, and much more. It explores advances in predictive analysis, such as using AI for leukemia detection and other diseases, strategic decision-making models using data analytics, video object detection using convolution, CNN-based mask detection, medical image watermarking using RDWT-SVD-DCT, and more.