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Data Mining with Computational Intelligence
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.
Explainable Artificial Intelligence for Intelligent Transportation Systems
Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can hardly be explained. This can be very problematic, especially for systems of a safety-critical nature such as transportation systems. Explainable AI (XAI) methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. FEATURES: Provides the necessary background for newcomers to the field (both academics and interested practitioners) Presents a timely snapshot of explainable and interpretable models in ITS applications Discusses ethical, societal, and legal implications of adopting XAI in the context of ITS Identifies future research directions and open problems
Computational Logistics
This book constitutes the refereed proceedings of the 6th International Conference on Computational Logistics, ICCL 2015, held in Delft, The Netherlands, in September 2015. The 50 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: transport over ground, transport over water, international coordination within a system, external coordination among systems.
Computational Intelligence in Optimization
This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.
Advances in Electrical Engineering and Computational Science
Advances in Electrical Engineering and Computational Science contains sixty-one revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Control Engineering, Network Management, Wireless Networks, Biotechnology, Signal Processing, Computational Intelligence, Computational Statistics, Internet Computing, High Performance Computing, and industrial applications. Advances in Electrical Engineering and Computational Science will offer the state of art of tremendous advances in electrical engineering and computational science and also serve as an excellent reference work for researchers and graduate students working with/on electrical engineering and computational science.
Evolutionary Computation in Data Mining
Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but a...
Maritime Decarbonization
This volume analyses maritime decarbonization from various perspectives. It contains unique approaches and tools in four areas: scenarios, value chains, enablers, and partnerships. Decarbonization has become a very important focus in the maritime industry. Anyone that delves into the topic quickly appreciates its breadth and complexity. Minimizing greenhouse gases (GHG) emissions in maritime practices at large and doing it swiftly is far from simple. The Paris 2015 climate goals and the IMO ambitions may be the industry’s guiding lights. But is this enough? Probably not. At the managerial level a paradigm shift is needed: from a fixed mindset that is calling for compensation to a growth mi...
Advances in Neural Networks - ISNN 2005
This book and its sister volumes constitute the proceedings of the 2nd International Symposium on Neural Networks (ISNN 2005). ISNN 2005 was held in the beautiful mountain city Chongqing by the upper Yangtze River in southwestern China during May 30–June 1, 2005, as a sequel of ISNN 2004 successfully held in Dalian, China.
Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Volume 1
This book contains a collection of the papers accepted in the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2014), which was held in Singapore from 10-12th November 2014. The papers contained in this book demonstrate notable intelligent systems with good analytical and/or empirical results.
Maritime Informatics
This first book on Maritime Informatics describes the potential for Maritime Informatics to enhance the shipping industry. It examines how decision making in the industry can be improved by digital technology, and introduces the technology required to make Maritime Informatics a distinct and valuable discipline. Based on participating in EU funded research over the last six years to improve the shipping industry, the editors stipulate that there is a need for the new discipline of Maritime Informatics, which studies the application of information systems to increasing the efficiency, safety, and ecological sustainability of the world’s shipping industry. This book examines competition and collaboration between shipping companies, and also companies who serve shipping needs, such as ports and terminals. Practical examples from leading experts give the reader real world examples for better understanding.
