Naiming Xie – författare

A book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly and concisely. Outlining a wide range of methods and models, it begins by examining the method of qualitative assessment. Next, it describes the process

A book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly and concisely. Outlining a wide range of methods and models, it begins by examining the method of qualitative assessment. Next, it describes the process and methods for building an index system of evaluation and considers the compared evaluation and the logical framework approach, analytic hierarchy process (AHP), and the data envelopment analysis (DEA) relative efficiency evaluation method.Unique in its emphasis on the practical applications of systems evaluation methods and models, the book introduces several new evaluation models of grey system, including general grey incidence model, grey incidence models based on similarity and closeness, grey cluster evaluation based on triangular whitenization functions, and multi-attribute grey target decision model. Explaining intricate concepts in language that is easy to understand it provides step-by-step explanations of the various methods and models.The text illustrates the practical application, analysis, and computation of systems evaluation methods and models with an abundance of practical examples and empirical studies. The case studies examine post evaluation of road-bridge construction projects, the efficiency evaluation of the science and technology activities, the evaluation of energy-saving projects in China, and the evaluation and selection of international cooperation projects.

A book in the Systems Evaluation, Prediction, and Decision-Making Series, Systems Evaluation: Methods, Models, and Applications covers the evolutionary course of systems evaluation methods, clearly and concisely. Outlining a wide range of methods and models, it begins by examining the method of qualitative assessment. Next, it describes the process and methods for building an index system of evaluation and considers the compared evaluation and the logical framework approach, analytic hierarchy process (AHP), and the data envelopment analysis (DEA) relative efficiency evaluation method.Unique in its emphasis on the practical applications of systems evaluation methods and models, the book introduces several new evaluation models of grey system, including general grey incidence model, grey incidence models based on similarity and closeness, grey cluster evaluation based on triangular whitenization functions, and multi-attribute grey target decision model. Explaining intricate concepts in language that is easy to understand it provides step-by-step explanations of the various methods and models.The text illustrates the practical application, analysis, and computation of systems evaluation methods and models with an abundance of practical examples and empirical studies. The case studies examine post evaluation of road-bridge construction projects, the efficiency evaluation of the science and technology activities, the evaluation of energy-saving projects in China, and the evaluation and selection of international cooperation projects.

This book reports on research findings and technologies supporting the paradigm shift toward the Factory of the Future. Gathering peer-review contributions to the 9th International Scientific-Technical Conference MANUFACTURING 2026, held on May 19-21, 2026, in Poznan, Poland, it covers advances in digital twins and virtual engineering, artificial intelligence applications in engineering design and management and advances in additive manufacturing technologies. It also discusses novel production monitoring systems, and strategies for operational excellence and logistics aimed at improving human-robot collaboration and/or fostering sustainable distribution networks. Offering a timely, practice-oriented reference guide for both researchers and practitioners in manufacturing, this book is also intended to bridge the gap between university and industry, fostering a closer communication and cooperation between them.

This book reports on research findings and technologies supporting the paradigm shift toward the Factory of the Future. Gathering peer-review contributions to the 9th International Scientific-Technical Conference MANUFACTURING 2026, held on May 19-21, 2026, in Poznan, Poland, it covers advances in digital twins and virtual engineering, artificial intelligence applications in engineering design and management and advances in additive manufacturing technologies. It also discusses novel production monitoring systems, and strategies for operational excellence and logistics aimed at improving human-robot collaboration and/or fostering sustainable distribution networks. Offering a timely, practice-oriented reference guide for both researchers and practitioners in manufacturing, this book is also intended to bridge the gap between university and industry, fostering a closer communication and cooperation between them.

This book aims to present an overview of grey system models for time series modelling and forecasting. It is about modelling and forecasting time series with ordinary differential equations, especially when the available samples are extremely limited. Grey system models (GSM) develop sequence operators to nonparametrically identify the underlying dynamics from the limited observations. This book concerns about two important modelling themes, small sample and poor information. The former focuses on the mechanism and methodology of GSMs for small-sample real-number time series, and the latter on the uncertainty quantification of grey number together with its small-sample modelling principles. In this book, a broad entry point to applied data science for students majoring in economic, management science, and engineering is applied, covering a wide range of topics from basic introductory material up to research-level techniques.

This book aims to present an overview of grey system models for time series modelling and forecasting. It is about modelling and forecasting time series with ordinary differential equations, especially when the available samples are extremely limited. Grey system models (GSM) develop sequence operators to nonparametrically identify the underlying dynamics from the limited observations. This book concerns about two important modelling themes, small sample and poor information. The former focuses on the mechanism and methodology of GSMs for small-sample real-number time series, and the latter on the uncertainty quantification of grey number together with its small-sample modelling principles. In this book, a broad entry point to applied data science for students majoring in economic, management science, and engineering is applied, covering a wide range of topics from basic introductory material up to research-level techniques.