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Ba Xi

Bio: Ba Xi is an academic researcher from North China Electric Power University. The author has contributed to research in topics: Financial risk & Real estate. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Papers
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Book ChapterDOI
17 Sep 2011
TL;DR: To break through conventional method, the calculation of the given demonstration example uses MATLAB 7.8, making the process more simple and quick, and manifested that the experiences of experts can be fully absorbed.
Abstract: Risk evaluation has been an important task for real estate investments in uncertain economic condition In order to find an effective method to deal with the uncertainty of risk evaluation, a model based on the AHP and the Grey system theory was proposed Though an example, we draw the conclusion that the evaluation result is in accordance with the fact To break through conventional method, the calculation of the given demonstration example uses MATLAB 78, making the process more simple and quick The result of the research has manifested that the experiences of experts can be fully absorbed The evaluation results become more accurate and conform to the realistic situation

3 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, two MCDM methods are applied in this research for decision making in high-tech industries in Iran and the final result shows that Nanotechnology is at the top of the list.
Abstract: One of the symbols of developed countries is high tech industries. High tech industries have a large margin. One of the priorities of developing countries is the progress in this type of industries. The decisions about priority of developing an industry are so hard that seems it should be seen from different perspectives. This research is focused on decision and policy making in priority of high tech industries in Iran. Two MCDM methods are applied in this research for decision making in this area. SWARA for evaluating and weighting criteria and COPRAS for evaluating and ranking alternatives are applied. Eleven experts from different fields participated in this research to make decision with SWARA and COPRAS. Four high tech industries including Biomedical Micro Electromechanical Systems (BioMEMS), Nano Technology, Biotechnology, and Biomedical Engineering were selected for this research. These industries were selected based on the potential of Iran. Final result shows that Nanotechnology is at the...

124 citations

Journal ArticleDOI
TL;DR: In this paper, an improved Analytical Hierarchy Process-group decision making (IAHP-GDM) model is proposed to reduce investment risk, which applies the method of least squares to adjust group decision matrix to satisfy the property of positive reciprocal matrix in AHP.
Abstract: Investment strategy selection relies heavily on personal experience and behavior. This paper proposes an improved Analytical Hierarchy Process-group decision making (IAHP-GDM) model to reduce investment risk. This model applies the method of least squares to adjust group decision matrix in order to satisfy the property of positive reciprocal matrix in AHP. In addition, five experts from related fields are invited to evaluate investment risk that takes group wisdom to eliminate personal bias. An empirical study is conducted to compare the proposed model to AHP for group decision making model. The results show that the IAHP-GDM model is not only accurate and effective, but also consistent with realistic investment environment.

64 citations

Journal ArticleDOI
Yi Wang1, Han Ding1, Fan Yang1
TL;DR: This paper proposed a evaluation method based on neural networks, based on the indexed of the analytic hierarchy process, through using the expert evaluation samples, by the BP neural network to study, so as to get the objective weight of the indexes, and then reflect the real situation of the evaluation objects.
Abstract: In human social life, it is often need to make comprehensive evaluation for person, thing , or a project to carry on the classification or evaluation. Analytic hierarchy process is relatively common and the most simple evaluation model. It draw up a series of evaluation index according to the evaluation object. The index may contain multiple child index, according to the relationship between the indexes or artificial factors to determine tie index weight, and get the overall evaluation for objects. The artificial factor is too much, it can not objectively reflect the real situation of the evaluation object. This paper proposed a evaluation method based on neural networks, based on the indexed of the analytic hierarchy process, through using the expert evaluation samples, by the BP neural network to study, so as to get the objective weight of the indexes, and then reflect the real situation of the evaluation objects.