The Experts below are selected from a list of 129 Experts worldwide ranked by ideXlab platform
Shucherng Fang - One of the best experts on this subject based on the ideXlab platform.
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optimization of fuzzy relation equations with max product composition
Fuzzy Sets and Systems, 2001Co-Authors: Jiranut Loetamonphong, Shucherng FangAbstract:Abstract An optimization problem with a linear objective function subject to a system of fuzzy relation equations using max-product composition is considered. Since the feasible domain is non-convex, traditional linear programming methods cannot be applied. We study this problem and capture some special characteristics of its feasible domain and the optimal solutions. Some procedures for reducing the original problem are presented. The problem is transformed into a 0–1 integer program which is then solved by the branch-and-bound method. For Illustration Purpose, an example of the procedures is provided.
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solving fuzzy relation equations with a linear objective function
Fuzzy Sets and Systems, 1999Co-Authors: Shucherng FangAbstract:Abstract An optimization model with a linear objective function subject to a system of fuzzy relation equations is presented. Due to the non-convexity of its feasible domain defined by fuzzy relation equations, designing an efficient solution procedure for solving such problems is not a trivial job. In this paper, we first characterize the feasible domain and then convert the problem to an equivalent problem involving 0–1 integer programming with a branch-and-bound solution technique. After presenting our solution procedure, a concrete example is included for Illustration Purpose.
Jing Liu - One of the best experts on this subject based on the ideXlab platform.
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metal substrate enhanced hydrogen production of aluminum fed liquid phase ga in alloy inside aqueous solution
International Journal of Hydrogen Energy, 2016Co-Authors: Xiaohu Yang, Bin Yuan, Jing LiuAbstract:Abstract Hydrogen is a kind of promising clean energy with huge potential values for human being. Developing a convenient real-time and on-demand hydrogen production and utilization method is critical for its wide practices. Liquid metal was recently found to be able to easily activate aluminum in aqueous solution to continuously and quickly generate hydrogen at room temperature, and thus provides a straightforward hydrogen production way. To further improve this technology, we are dedicated here to investigate the effects of the container substrate on such hydrogen generation process. An interesting phenomenon was found that metal substrate material would evidently enhance the hydrogen generation rate. For conceptual Illustration Purpose, comparative experiments were conducted to demonstrate the different hydrogen evolution modes between the present method and former approach, and the enhancement mechanism lying behind was revealed. In addition, the influence of the surface roughness of the substrate on the hydrogen production performance was also clarified. The present finding would help motivate an improved extremely simple, straightforward and low cost way for the liquid metal assisted aluminum hydrogen production.
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low melting point liquid metal as a new class of phase change material an emerging frontier in energy area
Renewable & Sustainable Energy Reviews, 2013Co-Authors: Shengfu Mei, Jing LiuAbstract:Abstract The application of phase change materials (PCMs) grew rapidly in the last few years, especially in those areas like solar energy, thermal comfort control, green building, environmental conservation and electronic cooling etc. Tremendous efforts have therefore been made on finding new powerful PCMs or improving performance of the currently available PCMs which generally subject to inherent defects, such as low thermal conductivity, poor stability after millions of repeated solidifying and melting processes, easy phase separation during transition and narrow temperature span between the melting point and the evaporation state. To better serve for the stringent request from many emerging utilization situations, this article is dedicated to systematically present a new class of high performance PCM, the low melting point liquid metals or their alloys, which were seldom addressed before. The unique merits, application features and potential values of these highly conductive liquid like materials were summarized with their basic properties interpreted. Some latest advancement made in the area was discussed for Illustration Purpose. Comparative evaluation on the fundamental mechanisms and practical issues between conventional PCMs and the low melting point metal PCM was carried out. Further, some involved scientific and technical challenges were raised. The present work is expected to incubate an emerging frontier towards studying and utilizing metal PCMs in the coming time, which is rather useful for a broad range of energy areas.
Muhammad Aslam - One of the best experts on this subject based on the ideXlab platform.
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a new attribute control chart using multiple dependent state repetitive sampling
IEEE Access, 2017Co-Authors: Mansour Sattam Aldosari, Muhammad AslamAbstract:In this paper, a new attribute control chart using multiple-dependent state repetitive sampling is designed. The operational procedure and structure of the proposed control chart is given. The required measures to determine the average run length for in-control and out-of-control processes are given. Tables of ARLs are reported for various control chart parameters. The proposed control chart is more sensitive in detecting a small shift in the process as compared with the existing attribute control charts. The simulation study shows the efficiency of the proposed chart over the existing charts. An example is given for Illustration Purpose.
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An Attribute Control Chart Based on the Birnbaum-Saunders Distribution Using Repetitive Sampling
IEEE Access, 2016Co-Authors: Muhammad Aslam, Osama H. ArifAbstract:In this paper, an attribute control chart using repetitive sampling is proposed when the lifetime of a product follows the Birnbaum-Saunders distribution. The number of failures is to be monitored by designing two pairs of upper and lower control limits. The necessary measurements are derived to assess the average run length (ARL). The various tables for ARLs are presented when the scale parameter and/or the shape parameter are shifted. The efficiency of the proposed control chart is compared with an existing chart. The proposed chart is shown to be more efficient than an existing control chart in terms of ARL. A real example is given for Illustration Purpose.
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designing of a hybrid exponentially weighted moving average control chart using repetitive sampling
The International Journal of Advanced Manufacturing Technology, 2015Co-Authors: Muhammad Azam, Muhammad Aslam, Chihyuck JunAbstract:A hybrid exponentially weighted moving average (HEWMA) control chart using repetitive sampling is presented in this manuscript. The designing of the proposed control chart is developed for a normally distributed quality characteristic. The formulas for the in-control and the out-of-control average run lengths (ARLs) are derived. Control chart coefficients are determined by considering the target in-control ARL. The tables for ARLs are presented for various target in-control ARLs and process shift parameters. The performance of the proposed control chart is compared with the existing control chart in terms of ARLs, which shows that the proposed chart performs better in detecting relatively small process mean shifts. An industrial example is given for the Illustration Purpose.
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Optimal designing of an SkSP-V skip-lot sampling plan with double-sampling plan as the reference plan
The International Journal of Advanced Manufacturing Technology, 2012Co-Authors: Muhammad Aslam, Munir Ahmad, Saminathan Balamurali, Mujahid RasoolAbstract:This paper deals with the optimal designing of a skip-lot sampling plan of type SkSP-V by considering the double-sampling plan as the reference plan. The design parameters are determined so as to minimize the average sample number while the specified producer’s risk and the consumer’s risks are satisfied. The tables are constructed by considering the various combinations of acceptable and limiting quality levels, and an example is given for Illustration Purpose. The advantages of the proposed plan over the conventional double-sampling plan are also discussed.
Jihui Yang - One of the best experts on this subject based on the ideXlab platform.
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posynomial fuzzy relation geometric programming
Soft Computing, 2007Co-Authors: Jihui Yang, Bingyuan CaoAbstract:In this paper, the concept and type of posynomial fuzzy relation geometric programming is introduced, some basic theories of posynomial fuzzy relation geometric programming is presented, and then a solution procedure is expatiated to solving such a programming based on structure of feasible region. And finally, two practical examples are given for Illustration Purpose.
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geometric programming with max product fuzzy relation equation constraints
North American Fuzzy Information Processing Society, 2005Co-Authors: Jihui Yang, Bingyuan CaoAbstract:An optimization model is presented with a polynomial objective function subject to max-product fuzzy relation equation. Then the structure of solution set and its solution method are related with max-product fuzzy relation equation. Next, the optimal solution is discussed, based on exponent of monomial among objective function, a solution procedure is proposed. And finally, two practical examples are given for Illustration Purpose.
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Geometric Programming with Fuzzy Relation Equation Constraints
The 14th IEEE International Conference on Fuzzy Systems 2005. FUZZ '05., 2005Co-Authors: Jihui YangAbstract:An optimization model is presented with a posynomial objective function subject to a fuzzy relation equation. Then the structure of solution set and its solving method are related about fuzzy relation equations. Next the optimum solution is discussed, based on exponent of monomial among objective function, then a solution procedure is proposed. And finally, two practical examples are given for Illustration Purpose
Kin Keung Lai - One of the best experts on this subject based on the ideXlab platform.
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credit risk evaluation using a weighted least squares svm classifier with design of experiment for parameter selection
Expert Systems With Applications, 2011Co-Authors: Lean Yu, Xiao Yao, Shouyang Wang, Kin Keung LaiAbstract:Support vector machines (SVM) is proved to be one of the most effective tool in credit risk evaluation. However, the performance of SVM is sensitive not only to the algorithm for solving the quadratic programming but also to the parameters setting in its learning machines as well as to the importance of different classes. In order to solve these issues, this paper proposes a weighted least squares support vector machine (LSSVM) classifier with design of experiment (DOE) for parameter selection for credit risk evaluation. In this approach, least squares algorithm is used to solve the quadratic programming, the DOE is used for parameter selection in SVM modelling and weights in LSSVM are used to emphasize the importance of difference classes. For Illustration Purpose, two publicly available credit datasets are selected to demonstrate the effectiveness and feasibility of the proposed weighted LSSVM classifier. The results show that the proposed weighted LSSVM classifier with DOE can produce the promising classification results in credit risk evaluation, relative to other classifiers listed in this study.
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a multiscale neural network learning paradigm for financial crisis forecasting
Neurocomputing, 2010Co-Authors: Shouyang Wang, Kin Keung Lai, Fenghua WenAbstract:A financial crisis is typically a rare kind of an event, but it hurts sustainable economic development when it occurs. This study proposes a multiscale neural network learning paradigm to predict financial crisis events for early-warning Purposes. In the proposed multiscale neural network learning paradigm, currency exchange rate, a typical financial indicator that usually reflects economic fluctuations, is first chosen. Then a Hilbert-EMD algorithm is applied to the currency exchange rate series. Using the Hilbert-EMD procedure, some intrinsic mode components (IMCs) of the currency exchange rate series, with different scales, can be obtained. Subsequently, the internal correlation structures of different IMCs are explored by a neural network model. Using the neural network weights, some important IMCs are selected as the final neural network inputs and some unimportant IMCs that are of little use in mapping from inputs to output are discarded. Using these selected IMCs, a neural network learning paradigm is used to predict future financial crisis events, based upon some historical data. For Illustration Purpose, the proposed multiscale neural network learning paradigm is applied to exchange rate data of two Asian countries to evaluate the state of financial crisis. Experimental results reveal that the proposed multiscale neural network learning paradigm can significantly improve the generalization performance relative to conventional neural networks.
