Author : Veli Himanen
Publisher : Routledge
Page : 367 pages
File Size : 10,60 MB
Release : 2019-07-09
Category : Social Science
ISBN : 0429817649
First published in 1998, this volume enters the debate on human behaviour in the form of neural networks in a spatial context. As most transportation research techniques had been developed in the 1960s and 1970s, these authors sought to bring that research into the modern era. Featuring 17 articles from 37 contributors, it begins with an overview and proceeds to examine aspects of travel behaviour, traffic flow and traffic management.
Author : Martin Laplante
Publisher :
Page : 180 pages
File Size : 11,21 MB
Release : 1991
Category : Expert systems (Computer science)
ISBN :
This project was conducted to sensitize transportation managers to the capabilities of neural network implementations through the production of educational materials and to identify transportation applications where a neural network implementation would provide an appropriate solution. The document contains a tutorial-type introduction to neural networks and describes the major classes of applications and types of neural networks, categorized as classification, prediction, sensor fusion, optimization, control, storage, and new computing paradigms. About 100 potential applications were found, about 12 of which are singled out for more detailed analysis.
Author : Dusan Teodorovic
Publisher : Springer Science & Business Media
Page : 401 pages
File Size : 34,53 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 9401144036
When solving real-life engineering problems, linguistic information is often encountered that is frequently hard to quantify using "classical" mathematical techniques. This linguistic information represents subjective knowledge. Through the assumptions made by the analyst when forming the mathematical model, the linguistic information is often ignored. On the other hand, a wide range of traffic and transportation engineering parameters are characterized by uncertainty, subjectivity, imprecision, and ambiguity. Human operators, dispatchers, drivers, and passengers use this subjective knowledge or linguistic information on a daily basis when making decisions. Decisions about route choice, mode of transportation, most suitable departure time, or dispatching trucks are made by drivers, passengers, or dispatchers. In each case the decision maker is a human. The environment in which a human expert (human controller) makes decisions is most often complex, making it difficult to formulate a suitable mathematical model. Thus, the development of fuzzy logic systems seems justified in such situations. In certain situations we accept linguistic information much more easily than numerical information. In the same vein, we are perfectly capable of accepting approximate numerical values and making decisions based on them. In a great number of cases we use approximate numerical values exclusively. It should be emphasized that the subjective estimates of different traffic parameters differs from dispatcher to dispatcher, driver to driver, and passenger to passenger.
Author : Robert Hecht-Nielsen
Publisher : Addison Wesley Publishing Company
Page : 456 pages
File Size : 47,60 MB
Release : 1990
Category : Computers
ISBN :
The areas covered here are those which are commonly managed by the generalist. The four contributions discuss: the autopsy in fatal non- missile head injuries; viral encephalitis and its pathology; a general approach to neuropathological problems; and dementia in middle and late life. Gives an overview of the network theory, including background review, basic concepts, associative networks, mapping networks, spatiotemporal networks, and adaptive resonance networks. Explores the principles of fuzzy logic. Annotation copyrighted by Book News, Inc., Portland, OR
Author : Vijendra Singh
Publisher : Springer Nature
Page : 625 pages
File Size : 43,33 MB
Release : 2020-08-19
Category : Technology & Engineering
ISBN : 9811568766
This book gathers selected high-quality research papers from the International Conference on Computational Methods and Data Engineering (ICMDE 2020), held at SRM University, Sonipat, Delhi-NCR, India. Focusing on cutting-edge technologies and the most dynamic areas of computational intelligence and data engineering, the respective contributions address topics including collective intelligence, intelligent transportation systems, fuzzy systems, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, and speech processing.
Author : Lingfei Wu
Publisher : Springer Nature
Page : 701 pages
File Size : 25,19 MB
Release : 2022-01-03
Category : Computers
ISBN : 9811660549
Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning. This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.
Author : R Beale
Publisher : CRC Press
Page : 260 pages
File Size : 19,77 MB
Release : 1990-01-01
Category : Mathematics
ISBN : 9781420050431
Neural computing is one of the most interesting and rapidly growing areas of research, attracting researchers from a wide variety of scientific disciplines. Starting from the basics, Neural Computing covers all the major approaches, putting each in perspective in terms of their capabilities, advantages, and disadvantages. The book also highlights the applications of each approach and explores the relationships among models developed and between the brain and its function. A comprehensive and comprehensible introduction to the subject, this book is ideal for undergraduates in computer science, physicists, communications engineers, workers involved in artificial intelligence, biologists, psychologists, and physiologists.
Author : Do, Quang Hung
Publisher : IGI Global
Page : 275 pages
File Size : 16,94 MB
Release : 2021-01-08
Category : Computers
ISBN : 1799832406
In today’s modernized market, various disciplines continue to search for universally functional technologies that improve upon traditional processes. Artificial neural networks are a set of statistical modeling tools that are capable of processing nonlinear data with strong accuracy. Due to their complexity, utilizing their potential was previously seen as a challenge. However, with the development of artificial intelligence, this technology has proven to be an effective and efficient problem-solving method. Artificial Neural Network Applications in Business and Engineering is an essential reference source that illustrates recent advancements of artificial neural networks in various professional fields, accompanied by specific case studies and practical examples. Featuring research on topics such as training algorithms, transportation, and computer security, this book is ideally designed for researchers, students, developers, managers, engineers, academicians, industrialists, policymakers, and educators seeking coverage on modern trends in artificial neural networks and their real-world implementations.
Author : Aura Reggiani
Publisher : Taylor & Francis
Page : 333 pages
File Size : 20,52 MB
Release : 2018-05-08
Category : Transportation
ISBN : 1351750569
This title was first published in 2001. A delightfully oriented selection of international state-of-the-art research in applied regional science, this informative volume places particular emphasis on the use of qualitative/quantitative methodologies in transportation and spatial dynamics. It presents new theoretical contributions in the context of spatial competition dynamics, particularly illustrating various combinations of methods and models regarding new measures of competition/cohesion in the two main fields of transportation and spatial dynamics.
Author : V.A Profillidis
Publisher : Elsevier
Page : 500 pages
File Size : 27,79 MB
Release : 2018-10-23
Category : Social Science
ISBN : 0128115149
Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers assess the validity and accuracy of demand forecasts. Forecasting and evaluating transport demand is an essential task of transport professionals and researchers that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand forecasts are necessary for companies and government entities when planning future fleet size, human resource needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport Demand help readers solve the problems they face on a daily basis. Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most suitable solution for all types of transport applications. - Presents the most recent and relevant findings and research - both at theoretical and practical levels - of transport demand - Provides a theoretical analysis and formulations that are clearly presented for ease of understanding - Covers analysis for all modes of transportation - Includes case studies that present the most appropriate formulas and methods for finding solutions and evaluating results
