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Additionally, there has been research into scientific and technological aspects of fuzzy theory by L. Zhang [ 14 ] and C. Chen [ 3 ].


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Fuzzy theory is applied to evaluation, though it lacks sufficient flexibility for evaluation of the main subject based on targets, stages or levels of evaluation, to fill which void, the approach of combined comprehensive evaluation model and the fuzzy control is applied for flexible and comprehensive green industry evaluation. This paper addresses several issues as follows.


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The green industry evaluation index set is presented in Section 3. The establishment of evaluation model is designed in Section 4. The application of green industry evaluation model is conducted in Section 5. And Section 6 presents the conclusion. The key to green industry assessment is choice of evaluation indices system, selected based on the characteristics and evaluation of the main objective facts.

The indices chosen comprehensively integrate those of foreign authorities [ 5, 7, 16—18 ] with those of domestic authority, according to the characteristics of the domestic green industry [ 1, 13 ]. There are many methods to determine the environmental weight of the green industry, which are best selected according to specific characteristics and particulars of the situation. We applied the analytic hierarchy process to determine green industry impact, due to a hierarchy inherent in the factors shown above.

The elements of each layer with respect to weighted layer criteria were deduced according to the maximum Eigen values and their Eigenvectors, applicable to the above matrix. Let Z denote the reviews ratings, i. Let p denote the number of the evaluation objects.

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If the index is in the middle of these evaluation levels, [ 2, 4, 6, 8, 10 ] can also be used. The fuzzy evaluation matrix was established to build an evaluation index, where the degree, r ij , of B ij belonging to comment, t , was obtained by expert evaluation method or the actual survey methods. The determined membership should then be divided into qualitative and quantitative indicators. Quantitative indicators may be divided into three types to determine their value: partial small, partial large and intermediate.

Model and application of green industry evaluation based on fuzzy control

To determine the appropriate membership functions, specific characteristics of the object may be compared with the above three class-types. Membership functions may then be determined by fuzzy statistical method or fuzzy distribution. Following are trapezoidal distribution formulas. The total of the fuzzy comprehensive evaluation model is given as Equation 4. The fuzzy control rule, which is actually stated set of multiple conditions, is an important part of the fuzzy control [ 4 ].

The data for this evaluation came from Dalian municipality, spanning —, selecting of expert evaluation method to evaluate the data and indicators. Due to space limitations, only the data from is given here to detail the evaluation process. In order to reduce the deviation of evaluated results, before evaluating green industry development, we applied the robust PLS approach [ 20 ], for prediction and diagnosis against outliers and missing KPI-related data.

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During the evaluation process, qualitative variables take five evaluation ratings. Index systems were rated using the Delphi method to represent expert opinion. The level proportion method was used to grade indexes. Statistical results are shown as follows. Based on the data above, the final results can be calculated as follows. In order to ensure the accuracy and reliability of the evaluation results, this paper applied FDI method [ 21 ] to process the entire data inspection. Since this data contains qualitative variables, many of which are factors beyond measure, this paper references data-driven design of robust fault detection system [ 19 ] to test the entire inspection process.

Results from the preceding showed no data-processing error, which indicates credible evaluation results.

Evaluation results can be obtained by fuzzy control rules. We believe this is to be caused by the rapid pace of industrial development causing increased waste emissions, while not being effectively controlled, thus reducing the level of evaluation. Additionally, the ratings for and were similar, due either to the number of factories reaching a stable level or effectively controlling waste emissions with an increase in number of factories.

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Nevertheless, the level of the green industry was in decline, and environmental pollution also may be intensified. As it can be seen from the above examples, the evaluated level of green industry in Dalian was low and showed a downward trend, suggesting that the local government should intensify supervision and management, and should encourage green business innovation and improvement, making for harmonious economic and environmental development.

Environmental protection and economic development are equally important for the survival of mankind. We cannot simply focus on the development of our basic needs while ignoring the quality of living space.

Advanced Fuzzy Logic Technologies in Industrial Applications Advances in Industrial Control

To evaluate the green industry, there is a need for greater in-depth and comprehensive understanding of the development of green industries, such that government may provide assistance to support environmental goals, and to encourage their creation. Horia-Nicolai Teodorescu. Home Contact us Help Free delivery worldwide.

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Fuzzy Logic Foundations and Industrial Applications

New Releases. Description Fuzzy Logic Foundations and Industrial Applications is an organized edited collection of contributed chapters covering basic fuzzy logic theory, fuzzy linear programming, and applications. Special emphasis has been given to coverage of recent research results, and to industrial applications of fuzzy logic. The chapters are new works that have been written exclusively for this book by many of the leading and prominent researchers such as Ronald Yager, Ellen Hisdal, Etienne Kerre, and others in this field.

Fuzzy Logic Applications in Flanges Manufacturing

The contributions are original and each chapter is self-contained. The authors have been careful to indicate direct links between fuzzy set theory and its industrial applications.


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Fuzzy Logic Foundations and Industrial Applications is an invaluable work that provides researchers and industrial engineers with up-to-date coverage of new results on fuzzy logic and relates these results to their industrial use. Product details Format Paperback pages Dimensions x x Other books in this series. Add to basket. Fuzzy Algorithms for Control H.

Fuzzy Modeling for Control Robert Babuska. Intelligent Systems and Interfaces H-. Advances in Computational Intelligence and Learning H. Fuzzy Databases Frederick E. Table of contents Foreword; G. Editor's Preface; Da Ruan. Part 1: Fuzzy Logic Foundations.