Advanced Data Mining and Applications


Book Description

This book constitutes the proceedings of the 16th International Conference on Advanced Data Mining and Applications, ADMA 2020, held in Foshan, China in November 2020. The 35 full papers presented together with 14 short papers papers were carefully reviewed and selected from 96 submissions. The papers were organized in topical sections named: Machine Learning; Text Mining; Graph Mining; Predictive Analytics; Recommender Systems; Privacy and Security; Query Processing; Data Mining Applications.




Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVIII


Book Description

This, the 28th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of six papers presented at the 26th International Conference on Database- and Expert-Systems Applications, DEXA 2015, held in Valencia, Spain, in September 2015. Topics covered include efficient graph processing, machine learning on big data, multistore big data integration, ontology matching, and the optimization of histograms for the Semantic Web.




Emerging Cutting-Edge Developments in Intelligent Traffic and Transportation Systems


Book Description

With the advent and development of AI and other new technologies, traffic and transportation have changed enormously in recent years, and the need for more environmentally-friendly solutions is also driving innovation in these fields. This book presents the proceedings of ICITT 2023, the 7th International Conference on Intelligent Traffic and Transportation, held from 18-20 September 2023 in Madrid, Spain. This annual conference is becoming one of the leading international conferences for presenting novel and fundamental advances in the fields of intelligent traffic and transportation. It also serves to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in intelligent traffic and transportation and related techniques. ICITT welcomes scholars and researchers from all over the world to share experiences and lessons with other enthusiasts, and develop opportunities for cooperation. The 27 papers included here represent an acceptance rate of 64% of submissions received, and were selected following a rigorous review process. Topics covered include autonomous technology; industrial automation; artificial intelligence; machine, deep and cognitive learning; distributed networking; transportation in future smart cities; hybrid vehicle technology; mobility; cyber-physical systems; design and cost engineering; enterprise information management; product design; intelligent automation; ICT-enabled collaborative global manufacturing; knowledge management; product-service systems; optimization; product lifecycle management; sustainable systems; machine vision; Industry 4.0; and navigation systems. Offering an overview of recent research and current practice, the book will be of interest to all those working in the field.




Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting


Book Description

This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.




Large Scale and Big Data


Book Description

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing t




Handbook on Artificial Intelligence and Transport


Book Description

With AI advancements eliciting imminent changes to our transport systems, this enlightening Handbook presents essential research on this evolution of the transportation sector. It focuses on not only urban planning, but relevant themes in law and ethics to form a unified resource on the practicality of AI use.




Reliability and Statistics in Transportation and Communication


Book Description

This book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice. The book presents the most relevant findings discussed at the 22nd International Multidisciplinary Conference on Reliability and Statistics in Transportation and Communication (RelStat), which took place on October 20 – 21, 2022, in Riga, Latvia, in hybrid mode. It spans a broad spectrum of advanced theories and methods, giving a special emphasis to the integration of artificial intelligent concepts into reliability approaches.




Choice Models in Marketing


Book Description

Choice Models in Marketing examines recent developments in the modeling of choice for marketing and reviews a large stream of research currently being developed by both quantitative and qualitative researches in marketing. Choice in marketing differs from other domains in that the choice context is typically very complex, and researchers' desire knowledge of the variables that ultimately lead to demand in marketplace. The marketing choice context is characterized by many choice alternatives. The aim of Choice Models in Marketing is to lay out the foundations of choice models and discuss recent advances. The authors focus on aspects of choice that can be quantitatively modeled and consider models related to a process of constrained utility maximization. By reviewing the basics of choice modeling and pointing to new developments, Choice Models in Marketing provides a platform for future research.