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Author: Aleksander Sładkowski
Publisher: Springer Nature
ISBN: 3031694872
Category :
Languages : en
Pages : 573
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Book Description
Author: Aleksander Sładkowski
Publisher: Springer Nature
ISBN: 3031694872
Category :
Languages : en
Pages : 573
Get Book Here
Book Description
Author: Aleksander Sładkowski
Publisher: Springer
ISBN: 9783031694868
Category : Computers
Languages : en
Pages : 0
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Book Description
This book focuses on the role of Artificial Intelligence in solving transportation problems and presents papers from around the world on AI in transportation. Currently, the development of computer technology and software has led to what can be said to be the beginning of a fundamentally new stage in science and technology. This new level is called “Artificial Intelligence (AI).” AI can be used in any area of human activity. One of the broadest uses of AI comes from transportation, broadly understood. Obviously, it is impossible to present all the possibilities of AI in the field of design, production and operation of transport in one book. But the authors of this monothematic monograph tried to describe achievements in their areas. In particular, the use of AI allows you to save energy and fuel when using vehicles, improve the preparation and implementation of transport processes, simplify warehouse operations, analyze and modernize existing transport infrastructure. These and other aspects of the use of AI in the transport industry are discussed in the monograph by specialists from Greece, China, Poland and other countries. This book can be recommended for study by scientists and professionals. It can also be selected by teachers as additional material when preparing relevant courses. Moreover, it can also be recommended for any readers seriously interested in the transportation industry.
Author: Guido Dartmann
Publisher: CRC Press
ISBN: 1000405656
Category : Technology & Engineering
Languages : en
Pages : 224
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Book Description
The book provides a broad overview of the challenges and recent developments in the field of smart mobility and transportation, including technical, algorithmic and social aspects of smart mobility and transportation. It reviews new ideas for services and platforms for future mobility. New concepts of artificial intelligence and the implementation in new hardware architecture are discussed. In the context of artificial intelligence, new challenges of machine learning for autonomous vehicles and fleets are investigated. The book also investigates human factors and social questions of future mobility concepts. The goal of this book is to provide a holistic approach towards smart transportation. The book reviews new technologies such as the cloud, machine learning and communication for fully atomatized transport, catering to the needs of citizens. This will lead to complete change of concepts in transportion.
Author: Phil Winder Ph.D.
Publisher: "O'Reilly Media, Inc."
ISBN: 1492072346
Category : Computers
Languages : en
Pages : 517
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Book Description
Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcement and enable a machine to learn by itself. Author Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; doesn't shy away from math and expects familiarity with ML. Learn what RL is and how the algorithms help solve problems Become grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learning Dive deep into a range of value and policy gradient methods Apply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learning Understand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and more Get practical examples through the accompanying website
Author: Min-wook Kang
Publisher: World Scientific
ISBN: 9813272821
Category : Technology & Engineering
Languages : en
Pages : 289
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Book Description
This monograph provides a comprehensive overview of methods for searching, evaluating, and optimizing highway location and alignments using genetic algorithms (GAs), a powerful Artificial Intelligence (AI) technique. It presents a two-level programming structure to deal with the effects of varying highway location on traffic level changes in surrounding road networks within the highway location search and alignment optimization process. In addition, the proposed method evaluates environmental impacts as well as all relevant highway costs associated with its construction, operation, and maintenance. The monograph first covers various search methods, relevant cost functions, constraints, computational efficiency, and solution quality issues arising from optimizing the highway alignment optimization (HAO) problem. It then focuses on applications of a special-purpose GA in the HAO problem where numerous highway alignments are generated and evaluated, and finally the best ones are selected based on costs, traffic impacts, safety, energy, and environmental considerations. A review of other promising optimization methods for the HAO problem is also provided in this monograph.
Author: Pandian Vasant
Publisher:
ISBN: 9781685072117
Category : Computers
Languages : en
Pages : 0
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Book Description
This book presents the latest research in the field of machine learning, discussing the real-world application problems associated with new innovative renewable energy methodologies as well as cutting edge technologies in the transport industry. The requirements and demands of problem solving have been increasing exponentially, and new artificial intelligence and machine learning technologies have reduced the scope of data coverage worldwide. Recent advances in data technology (DT) have contributed to reducing the gaps in the coverage of domains around the globe. Attention to clean energy in recent decades has been growing exponentially. This is mainly due to a decrease in the cost of both installed capacity of converters and a decrease in the cost of generated energy. Such successes were achieved thanks to the improvement of modern technologies for the production of converters, an increase in the efficiency of using incoming energy, optimisation of the operation of converters and analysis of data obtained during the operation of systems with the possibility of planning production. The use of clean energy plays an important role in the transportation industry, where technologies are also being improved from year to year - the transportation industry is growing, and machinery and systems are becoming more autonomous and robotic, where it is no longer possible to do without complex intelligent computing, machine learning optimisation, planning and working with large amounts of data. The book is a valuable reference work for researchers in the fields of renewable energy, computer science and engineering with a particular focus on machine learning and intelligent optimization as well as for postgraduates, managers, economists and decision makers, policy makers, government officials, industrialists and practicing scientists and engineers as well compassionate global decision makers. Topics include: Machine learning, Quantum Optimization, Modern Technology in Transport Industry, Innovative Technologies in Transport Education, Systems Based on Renewable Energy Conversion, Business Process Models and Applications in Renewable Energy, Clean Energy, and Climate Change.
Author: Said Broumi
Publisher: CRC Press
ISBN: 1040043062
Category : Computers
Languages : en
Pages : 348
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Book Description
Zadeh introduced in 1965 the theory of fuzzy sets, in which truth values are modelled by numbers in the unit interval [0, 1], for tackling mathematically the frequently appearing in everyday life partial truths. In a second stage, when membership functions were reinterpreted as possibility distributions, fuzzy sets were extensively used to embrace uncertainty modelling. Uncertainty is defined as the shortage of precise knowledge or complete information and possibility theory is devoted to the handling of incomplete information. Zadeh articulated the relationship between possibility and probability, noticing that what is probable must preliminarily be possible. Following the Zadeh’s fuzzy set, various generalizations (intuitionistic, neutrosophic, rough, soft sets, etc.) have been introduced enabling a more effective management of all types of the existing in real world uncertainty. This book presents recent theoretical advances and applications of fuzzy sets and their extensions to Science, Humanities and Education. This book: Presents a qualitative assessment of big data in the education sector using linguistic Quadri partitioned single valued neutrosophic soft sets. Showcases application of n-cylindrical fuzzy neutrosophic sets in education using neutrosophic affinity degree and neutrosophic similarity Index. Covers scientific evaluation of student academic performance using single value neutrosophic Markov chain. Illustrates multi-granulation single-valued neutrosophic probabilistic rough sets for teamwork assessment. Examines estimation of distribution algorithm based on multiple attribute group decision-making to evaluate teaching quality. It is primarily written for Senior undergraduate and graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering.
Author: Goutam Sanyal
Publisher: Springer Nature
ISBN: 9811685428
Category : Technology & Engineering
Languages : en
Pages : 555
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Book Description
This book comprises select papers from the International Conference on Artificial Intelligence and Sustainable Engineering (AISE 2020). The volume focuses on the recent advancements in artificial intelligence and addresses how it is useful in achieving truly sustainable solutions. The key strands of this book include artificial intelligence in healthcare, IoT for modern life, security and surveillance, big data analytics, machine learning and computing, communication technologies, gesture technology, virtual intelligence, and audio & speech processing. The book addresses sustainability challenges in various computing techniques and opportunities for sustainable engineering based on AI and supporting tools such as engineering design for sustainable development using IoT/AI, smart cities: waste minimization, remanufacturing, reuse and recycling technologies using IoT/AI, industry 4.0, intelligent and smart grid systems, energy conservation using technology, green engineering/technology, robotic process automation (RPA) and water and air quality management. This book can be a valuable resource for academicians, researchers, and professionals working in AI and its applications.
Author: Chee Peng Lim
Publisher: Springer Science & Business Media
ISBN: 3642136397
Category : Technology & Engineering
Languages : en
Pages : 539
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Book Description
Decision making arises when we wish to select the best possible course of action from a set of alternatives. With advancements of the digital technologies, it is easy, and almost instantaneous, to gather a large volume of information and/or data pertaining to a problem that we want to solve. For instance, the world-wi- web is perhaps the primary source of information and/or data that we often turn to when we face a decision making problem. However, the information and/or data that we obtain from the real world often are complex, and comprise various kinds of noise. Besides, real-world information and/or data often are incomplete and ambiguous, owing to uncertainties of the environments. All these make decision making a challenging task. To cope with the challenges of decision making, - searchers have designed and developed a variety of decision support systems to provide assistance in human decision making processes. The main aim of this book is to provide a small collection of techniques stemmed from artificial intelligence, as well as other complementary methodo- gies, that are useful for the design and development of intelligent decision support systems. Application examples of how these intelligent decision support systems can be utilized to help tackle a variety of real-world problems in different - mains, e. g. business, management, manufacturing, transportation and food ind- tries, and biomedicine, are also presented. A total of twenty chapters, which can be broadly divided into two parts, i. e.
Author: Nguyen, Tien V. T.
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 528
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Book Description
In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.
