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Transfer Model Updating with Aggregate Data

Transfer Model Updating with Aggregate Data PDF Author: Frank S. Koppelman
Publisher:
ISBN:
Category : Choice of transportation
Languages : en
Pages : 30

Book Description


Transfer Model Updating with Aggregate Data

Transfer Model Updating with Aggregate Data PDF Author: Frank S. Koppelman
Publisher:
ISBN:
Category : Choice of transportation
Languages : en
Pages : 30

Book Description


Modelling Transport

Modelling Transport PDF Author: Juan de Dios Ortúzar
Publisher: John Wiley & Sons
ISBN: 1119993520
Category : Technology & Engineering
Languages : en
Pages : 584

Book Description
Already the market leader in the field, Modelling Transport has become still more indispensible following a thorough and detailed update. Enhancements include two entirely new chapters on modelling for private sector projects and on activity-based modelling; a new section on dynamic assignment and micro-simulation; and sizeable updates to sections on disaggregate modelling and stated preference design and analysis. It also tackles topical issues such as valuation of externalities and the role of GPS in travel time surveys. Providing unrivalled depth and breadth of coverage, each topic is approached as a modelling exercise with discussion of the roles of theory, data, model specification, estimation, validation and application. The authors present the state of the art and its practical application in a pedagogic manner, easily understandable to both students and practitioners. Follows on from the highly successful third edition universally acknowledged as the leading text on transport modelling techniques and applications Includes two new chapters on modelling for private sector projects and activity based modeling, and numerous updates to existing chapters Incorporates treatment of recent issues and concerns like risk analysis and the dynamic interaction between land use and transport Provides comprehensive and rigorous information and guidance, enabling readers to make practical use of every available technique Relates the topics to new external factors and technologies such as global warming, valuation of externalities and global positioning systems (GPS).

Optimization and Discrete Choice in Urban Systems

Optimization and Discrete Choice in Urban Systems PDF Author: Bruce G. Hutchinson
Publisher: Springer Science & Business Media
ISBN: 3642510205
Category : Business & Economics
Languages : en
Pages : 381

Book Description
'l'he papers contained in this volume were originally presented at the International symposium on New Directions in Urban Systems Modelling held at the University of Waterloo in July, 1983. The papers have been reviewed and rewritten since that time. The exception is the introductory paper written specially by Manfred Fischer and Peter Nijkamp as an introduction to this volume. The manuscript was prepared in the word processing unit in the nepartment of Civil Engineering, university of Waterloo. The sustained work of Mrs. I. Steffler in preparing this manuscript is gratefully acknowledged. "'r. R. K. Kumar provided excellent assistance with the editorial process. The svrnposium and the preparation of this manuscript were supporteö financially by the Natural Sciences and Engineering Research Council of Canada, The Academic Development Fund and the Department of Civil Engineering, TTniversity of waterloo. TABLE OF CONTENTS PREFACE •....••...•..•...•..........•..••.•....•.•••.••.••.•..•••••.•.••.. III Categorical Data and Choice Analysis in a Spatial Context Manfred Fischer and Peter Nijkamp .•••....•.......•.•.....•.......•.......

Updating of Parameters in Aggregate Total Demand Models

Updating of Parameters in Aggregate Total Demand Models PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 9

Book Description
Research on demand-model transferability has consistently shown that the updated models perform better than the simple transfer of the original model with the original coefficients. Several methods are available for the updating of parameter estimates during model transfer. The scalar factor method has been extended to specify individual factors for each variable. This method allows the flexibility of removing insignificant variables in transfer; it also permits the grouping of parameters that have to be updated by a common factor. INdividual scalar factors can also be identified for variables that are uniquely affected during transfer. This approach therefore incorporates the strength of both the sample data and the calibration model to its maximum showing that this method gives excellent fit to observed flows when tested for geographical transferability of an aggregate intercity total demand model for public transport in Sri Lanka. It is also shown that the Bayesian method becomes less efficient when sample sizes available for updating become smaller.

Simplified Transport Demand Modelling

Simplified Transport Demand Modelling PDF Author: Juan de Dios Ortúzar S.
Publisher:
ISBN:
Category : Communication and traffic
Languages : en
Pages : 162

Book Description


Federated and Transfer Learning

Federated and Transfer Learning PDF Author: Roozbeh Razavi-Far
Publisher: Springer Nature
ISBN: 3031117484
Category : Technology & Engineering
Languages : en
Pages : 371

Book Description
This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.

Federated Deep Learning for Healthcare

Federated Deep Learning for Healthcare PDF Author: Amandeep Kaur
Publisher: CRC Press
ISBN: 104012612X
Category : Computers
Languages : en
Pages : 267

Book Description
This book provides a practical guide to federated deep learning for healthcare including fundamental concepts, framework, and the applications comprising domain adaptation, model distillation, and transfer learning. It covers concerns in model fairness, data bias, regulatory compliance, and ethical dilemmas. It investigates several privacy-preserving methods such as homomorphic encryption, secure multi-party computation, and differential privacy. It will enable readers to build and implement federated learning systems that safeguard private medical information. Features: Offers a thorough introduction of federated deep learning methods designed exclusively for medical applications. Investigates privacy-preserving methods with emphasis on data security and privacy. Discusses healthcare scaling and resource efficiency considerations. Examines methods for sharing information among various healthcare organizations while retaining model performance. This book is aimed at graduate students and researchers in federated learning, data science, AI/machine learning, and healthcare.

Intelligent Computing and Optimization

Intelligent Computing and Optimization PDF Author: Pandian Vasant
Publisher: Springer Nature
ISBN: 3031503309
Category : Technology & Engineering
Languages : en
Pages : 378

Book Description
This book of Springer Nature is another proof of Springer’s outstanding greatness on the lively interface of Holistic Computational Optimization, Green IoTs, Smart Modeling, and Deep Learning! It is a masterpiece of what our community of academics and experts can provide when an interconnected approach of joint, mutual, and meta-learning is supported by advanced operational research and experience of the World-Leader Springer Nature! The 6th edition of International Conference on Intelligent Computing and Optimization took place at G Hua Hin Resort & Mall on April 27–28, 2023, with tremendous support from the global research scholars across the planet. Objective is to celebrate “Research Novelty with Compassion and Wisdom” with researchers, scholars, experts, and investigators in Intelligent Computing and Optimization across the globe, to share knowledge, experience, and innovation—a marvelous opportunity for discourse and mutuality by novel research, invention, and creativity. This proceedings book of the 6th ICO’2023 is published by Springer Nature—Quality Label of Enlightenment.

Blockchains

Blockchains PDF Author: Anwer Al-Dulaimi
Publisher: John Wiley & Sons
ISBN: 1119781019
Category : Technology & Engineering
Languages : en
Pages : 420

Book Description
Blockchains Empowering Technologies and Industrial Applications A comprehensive guide to the most recent developments in blockchains in theoretical and industrial perspectives Originally introduced as a method to keep track of Bitcoin transactions over a peer-to-peer network, blockchain is a continuously growing list of records, called blocks, which are linked and secured using cryptography into a chain held in public databases. The use of this technology has grown since its cryptocurrency creation and now store three types of information: 1) transactions, including the date, time, and value of purchases; 2) records of participates in transactions; and 3) unique code known as a “hash” that distinguishes one block from another. A single block on the blockchain can hold 1 MB of data, or potentially thousands of transactions — this then can allow for hundreds of thousands of transactions to be recorded as each block can join the state-of-the-art blockchain. Blockchains provides a detailed overview of the latest and most innovative concepts, techniques, and applications related to the developing blockchain. Aimed at novices and experts on the subject, the book focuses on blockchain technologies, integrated systems, and use cases, specifically by looking at three major technical areas: blockchain platforms and distributed database technologies, consensus and fault tolerance, and Blockchain as a Service (BaaS). These avenues of research are essential to support blockchain functionalities, such as acquiring and updating existing data, securing data resources and the recovery of failures, and using blockchains in various services that range from cryptocurrencies to cloud automation. Blockchains readers will also find: Brainstorming activities that gradually builds the knowledge of readers on the described technology and deployment scenarios Investigation of specific topics such as novel networking protocols, wireless techniques, new infrastructure designs, operations management, and deployment strategies Discussion of technical challenges in blockchain, as well as how to manage cloud-based networks, service automation, and cyber security Numerous elementary and advanced examples on various topics at the end of the book that can be used for training purposes Illustrations including tables and diagrams to help elucidate points made throughout the volume Glossary of relevant terminology to blockchains in enterprise Blockchains is a useful reference for researchers in vehicular networking and computer science, as well as cloud storage providers and governmental offices for data management.

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing PDF Author: Sudeep Pasricha
Publisher: Springer Nature
ISBN: 303140677X
Category : Technology & Engineering
Languages : en
Pages : 571

Book Description
This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.