Reformative Financial Risk Management Approach： A Multistage Decision Support System with the Assistance of Fuzzy Goal Programming and Expertons Method

The potential demand on financial risk management has being increased considerably by the reason of Basel 11 regulations and instabilities in economy. In recent years, financial institutions and companies have been struggled for building up intensive financial risk management tools due to Basel II guidance on establishing financial self-assessment systems. In this respect, decision support system has a significant role on effectuating intensive financial risk management roadmap. In this study, a reformative financial risk management system is presented with the combination of determining financial risks with their importance, calculating risk scores and making suggestions based on detected risk scores by applying corrective actions. First, financial risk factors and indicators of these risk variables are selected and weights of these variables are specified by using fuzzy goal programming. After that, total risk scores are calculated and amendatory financial activities are appeared by means of expertons method which also provides possibilities of the alternative decisions. To illustrate the performance of integrated and multistage decision support system, a survey is applied on the end users.

A Decision Support System for Selection of Solar Power Plant Locations by Applying Fuzzy AHP and TOPSIS: An Empirical Study

The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.

GA-Fuzzy Decision Support System for Mercury Removal in Natural Waters

The idea of this research is to apply sustainability and augment efficiency of the aquatic systems by intelligent tools. This paper exploits fuzzy logic approach as a flexible methodology for providing supplementary information about mercury removal in natural waters. Fuzzy logic generates information on Hg behaviour in water according to its uptake by bio-species and adsorption by sediments. Fuzzy Decision Support System (FDSS) comprises knowledge base (i.e. premises and conclusions), fuzzy sets, and fuzzy rules. Knowledge base and rules are being built manually and by algo- rithm. GA-FDSS incorporates genetic algorithm GA to build optimal approximation for knowledge base, fuzzy sets, and rules. The role of integrating GA with FDSS is to train knowledge base and rules automatically from available data, hence FDSS models and predicts conclusion acquired. The findings of this research show more than 95% correlation between observed data and soft computed data. The optimal biological uptake occurs at pH of 5.5. The optimal sedi-ment adsorption occurs at pH of 8. The final mercury concentration calculated in natural waters is about 7 ? 10–8 mole/L. The results show that the removal efficiency of mercury by natural waters approaches 97%. Consequently the obtained fuzzy logic informative hierarchy is proficient to manage metals removal by aquatic systems.

A cloud-based fuzzy approach for spatial site selection in decision support system

In decision support system for spatial site selection, the fuzzy synthetic evaluation is a useful way. However, the method can’t pay attention to the randomness in factors. To remedy the problem, this paper proposes a clouded-base fuzzy approach which combines advantages of cloud transform and fuzzy synthetic evaluation. The cloud transform considers the randomness in the factors and product the higher concept layer for data mining. At the same time, the check mechanism controls the quality of partitions in factors. Then the fuzzy approach was used to get final evaluation value with randomness and fuzziness. It make the final result is optimization. Finally, performance evaluations show that this approach spent less runtime and got more accuracy than the fuzzy synthetic. The experiments prove that the proposed method is faster and more accuracy than the original method.

基于Fuzzy Petri网专家系统的研究

提出采用ＦｕｚｚｙＰｅｔｒｉ网作为知识表示和推理机制的模型，发挥其较好的模型描述和能处理并行推理的特点。基于ＦｕｚｙＰｅｔｒｉ网构造了一个耦合结构的专家数据库系统（ＥＤＢＳ），提高了推理的效率及其准确性，同时具有并发控制、数据组织、共享、存取和查询等数据库管理系统的功能，并使用投资决策实例对模型进行了解释和验证。

Assessing Watershed Vulnerability in Bernalillo County, New Mexico Using GIS-Based Fuzzy Inference

Watershed vulnerability was assessed for Bernalillo County, New Mexico using a multi-criteria Fuzzy Inference System (FIS) implemented in a Geographic Information System (GIS). A vulnerability map was produced by means of a weighted overlay analysis that combined soil erosion and infiltration maps derived from the FIS methodology. Five vulnerability classes were stipulated in the model: not vulnerable (N), slightly vulnerable (SV), moderately vulnerable (MV), highly vulnerable (HV), and extremely vulnerable (EV). The results indicate that about 88% of the study area is susceptible to slight (SV) to moderate vulnerability (MV), with 11% of the area subject to experience high or extreme vulnerability (HV/EV). For land use and land cover (LULC) classifications, shrub land was identified to experience the most vulnerability. Weighted overlay output compared similarly with the results predicted by Revised Universal Soil Loss Equation (RUSLE) model with the exception of the not vulnerable (N) class. The eastern portion of the county was identified as most vulnerable due to its high slope and high precipitation. Herein, structural stormwater control measures (SCMs) may be viable for managing runoff and sediment transport offsite. This multi-criteria FIS/GIS approach can provide useful information to guide decision makers in selection of suitable structural and non-structural SCMs for the arid Southwest.

Evaluating Watershed Vulnerability in Bernalillo County, New Mexico Using Expert Testimony, Fuzzy Analytic Hierarchy Process, and GIS

Geographic Information System (GIS) software was used to create a watershed vulnerability model for Bernalillo County, New Mexico. Watershed vulnerability was investigated as a function of soil erosion and infiltration criteria: precipitation, land slope, soil erodibility (K-factor), vegetation cover (NDVI), land use, drainage density, saturated hydraulic conductivity, and hydrologic soil group. Respective criteria weights were derived using a Fuzzy Analytic Hierarchy Process (FAHP) supported by expert opinion. A survey of 10 experts, representing New Mexico Institute of Mining and Technology (NMT), the New Mexico Bureau of Geology and Mineral Resources (NMBGMR), and the United States Geologic Survey (USGS), provided model input data for an integrated pair-wise comparison matrix for soil erosion and for infiltration. Individual criteria weights were determined by decomposing the respective fuzzy synthetic extent matrix using the centroid method. GIS layers were then combined based on criteria weights to produce maps of soil erosion potential and infiltration potential. A composite watershed vulnerability map was generated by equal weighting of each input map. Model results were categorized into five vulnerability categories: not vulnerable (N), slightly vulnerable (SV), moderately vulnerable (MV), highly vulnerable (HV), and extremely vulnerable (EV). The resulting FAHP/GIS model was used to generate a watershed vulnerability map of discrete areas in Bernalillo County, which may be vulnerable to stormwater run-off events and soil erosion. Such high volume run-off events can cause erosion damage to property and infrastructure. Alternatively, in areas near urban development, stormwater run-off may contribute non-point-source pollutant contamination of New Mexico’s surface water resources. The most problematic areas in Bernalillo County are present in the Eastern and Northwestern portions. However, less than 1% of the total area lies within the lowest and highest vulnerability categories with the majority centered around moderate vulnerability. The results of the model were compared with a previously published crisp AHP method. Both methods showed similar regional vulnerability trends. This MCDS/GIS approach is intended to provide support to local governments and decision makers in selection of suitable structural or nonstructural stormwater control measures.

ANINTELLIGENT DECISION SUPPORTSYSTEM（IDSS） ONTHEPROCESSOFNICKELMATTESMELTER

This paper describes the structure and function of the intelligent decision support system (IDSS) on the process of nickel matte smelter. The knowledge and model base system based on fuzzy-decision rules ale specially suggested. The IDSS possesses the self-learning and adaptive properties, andhas been used for managing and analyzing the production information, optimizing the composition of the charge mixture, and deciding the optimal operational conditions. Electric energy consumption has been reduced remarkably and the yield of nickel has been increased.

AN INTELLIGENT DECISION SUPPORT SYSTEM （IDSS） IN THE OPERATION PROCESS OF ELECTRIC FURNACE FOR CLEANING SLAG

In this paper, the structure and function of the IDSS in the operation process of electric furnace for cleaning slag are presented and the fuzzy neural network decision model (FNNDM) in the IDSS is specially suggested. The IDSS possesses selflearning and adaptive properties, and has been used for managing and analyzing the optimal operational conditions since June 1992. Electric energy consumption has been reduced remarkably and the coefficient of recovery of cobalt and nickel has been increased.

FUZZY ADAPTIVE CONTROL MODEL FOR PROCESS IN NICKEL MATTE SMELTING FURNACE

ＦＵＺＺＹＡＤＡＰＴＩＶＥＣＯＮＴＲＯＬＭＯＤＥＬＦＯＲＰＲＯＣＥＳＳＩＮＮＩＣＫＥＬＭＡＴＴＥＳＭＥＬＴＩＮＧＦＵＲＮＡＣＥＭｅｉ，ＣｈｉＰｅｎｇ，ＸｉａｏｑｉＺｈｏｕ，Ｊｉｅｍｉｎ（ＤｅｐａｒｔｍｅｎｔｏｆＡｐｐｌｉｅｄＰｈｙｓｉｃｓａｎｄＨｅａ...

Effectiveness of Fuzzy Overlay Function for Multi-Criteria Spatial Modeling—A Case Study on Preparation of Land Resources Map for Mawsynram Block of East Khasi Hills District of Meghalaya, India

Multi-criteria spatial modeling is one of the important components of spatial decision support system (SDSS). Multi-criteria spatial modeling often requires a common scale of values for diverse and dissimilar inputs to create an integrated analysis. Weighted overlay function is most commonly used for site suitability analysis which identifies the most preferred locations for a specific phenomenon. However, weighted overlay function gives inconsistent and erroneous results for highly dissimilar inputs as it assumes that most favorable factors result in the higher values of raster, while identifying the best sites. This paper conveys the effectiveness of fuzzy overlay function for multi-criteria spatial modeling. It is based on the principle of fuzzy logic theory which defines membership using Gaussian function on each of the input rasters instead of giving individual rank to them like in weighted overlay function. A case study on preparation of land resources map for Mawsynram block of East Khasi Hills district of Meghalaya, India is presented here. It was observed that fuzzy overlay function has given more satisfactory output in terms of site suitability while comparing with the result of weighted overlay function.

Online Dispatching Decision Support System for Smart Grid Reservoir Group

Based on the full use of historical reservoir dispatching information, artificial intelligence is applied to grid reservoir group dispatching. A knowledge representation method, which combines dispatching rules and intelligence models, is put forward. The intelligent dispatching system is established and the system architecture is presented. Additionally, the acquisition, representation and reasoning mechanism of reservoir dispatching knowledge are designed in detail.

A knowledge-based decision support system for engineering design

A knowledge-based decision supporting system, used for engineering design is introduced by describing the architecture, function, workflow of the system and its way of implementation. Based upon information composed of knowledge, models, data, cases, methods, etc, the system is designed to use such methods as knowledge-based reasoning, case-based reasoning, and multi-criteria evaluation techniques to provide effective tools to support the decision-making process.

The Intelligent Decision Support System Model of SARS

Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper.This model can be used not only for SARS but also for other paroxysmal accidences.

Research on and implementation of a knowledge-reasoning based evaluation support system

An evaluation support system involving complicated decision making problems during engineering design of products is introduced by first describng and modeling complicated decision making problems, and then constructing and describing the architecture and functional structure of an evaluation support system, based on knowledge-based reasoning. Knowledge contains important experience of field-expert and can be classified and stored in knowledge bases, and therefore, the system suggests information-processing tools based on information resources including data knowledge bases and methods bases, which can be used to evaluate the designs against the multi-criteria decision framework thereby providing decision-makers with rational and scientific information.

Integrating Knowledge－Based Simulation with Aspiration－Directed Model－based Decision Support System

This paper reports an aspiration-directed, model-based decision support system (AMDSS) integrated with a knowledge-based simulation system. The system is designed to study China's mid-range economic development strategy. The capacity of the system is enhanced by the knowledge-based component which provides a knowledge-based simulation environment for model management. Currently the system has passed the stage of prototype and achieves its implementation capacity. The paper first presents the mathematical aspects of decision making including aspiration-directed decision making, then discusses the architecture of the system. The purpose of the paper is to provide insights into how such an integrated system could provide decision support for complex decision analysis.

Adaptive support vector machine decision feedback equalizer

An adaptive support vector machine decision feedback equalizer（ASVM-DFE） based on the least square support vector machine（LS-SVM） is proposed,it solves linear system iteratively with less computational intensity.An adaptive non-singleton fuzzy support vector machine decision feedback equalizer（ANSFSVMDFE） is also presented,it adopts the non-singleton fuzzy Gaussian kernel function with similar characteristic of pre-filter and is modified with a space transformation based approach.Simulations under nonlinear time variant channels show that ASVM-DFE and ANSFSVM-DFE perform very well on nonlinear equalization and ANSFSVM-DFE acts especially well in resisting abrupt interference.

Combining Knowledge-and Data-Driven Fuzzy Approach to Evaluate Shelf-Life of Various Seafood Products

Due to the complexity of the deterioration process of seafood products,relying on one indicator is not adequate to determine the quality of such products.Usually,shelf-life was estimated based on various indicators complicating the decision-making process.Decision Support Systems are considered as a good solution.The current study aims to establish a simple and novel fuzzy model based on a combination of knowledge-and data-driven approaches to define a fuzzy quality deterioration index(FQDI)in various seafood products(rainbow trout,threadfin bream,and white shrimp samples)during cold storage.Total volatile basic nitrogen(TVB-N)and psychrotrophic microorganisms counts(PMCs)were determined based on traditional methods.The sensory analysis was performed by a data-driven fuzzy approach.Overall,the shelf-life of the rainbow trout fillet was estimated to be 8 d,based on all the freshness parameters.However,the shelf-life of the Japanese threadfin bream fillet was 5-7 d according to the microbial and chemical parameters,respectively.This time for shrimp samples was 6-8 d using sensory score and TVB-N contents.The results of data-driven fuzzy approach showed all of the quality properties were considered as the'Important'-'Very Important'(defuzzification score>75).The TVB-N and PMCs were the most and weakest freshness quality properties(defuzzified-values:84.64 and 78.75,respectively).Based on FQDI,the shelf-life of the rainbow trout,Japanese threadfin bream,and shrimp samples were estimated to be 8,5,and 7 d,respectively.This method was able to successfully provide a comprehensive deterioration index for evaluating the seafood shelf-life.Such a total index can be considered as a comprehensive output(y variable)to predict seafood freshness by rapid and nondestructive method.

中日地区主导型可再生能源项目的经济增加值与推广策略比较研究

文章以长阳县、挂川市和唐津市为例,按照各项目实施的顺序,对社会接受度、利益相关方管理、脱碳化的优点、收益返还方式等进行比较分析,构建地区主导型可再生能源项目模式.比较中日地区主导型可再生能源项目的经济增加值.结果表明,政府参与度、商业可行性和地区增加值之间存在一定的关系.通过地区能源推广策略的评价模型和非结构化模糊决策支持系统,以各地区的推广策略和经济效益为标准,对具体的能源推广策略的优先顺序进行排名.最后,从限制因素、节能政策、产业链发展等多角度进行综合比较分析,提出了中日地区主导可再生能源项目的推广策略.

基于多Agent的企业市场营销决策支持系统设计

由于当前已有系统未能采用模糊调整-模拟反馈方法对市场需求进行预测,导致企业市场营销决策支持错误率和响应时间上升、可靠性下降,为此提出一种基于多Agent的企业市场营销决策支持系统,结合Agent技术和理论进行设计,详细阐述系统的具体操作流程。通过模糊调整-模拟反馈方法对企业市场需求进行预测,调整市场营销策略,确定营销计划,最终实现企业市场营销决策支持系统设计。仿真实验结果表明,所设计系统能够有效提升系统的可靠性,同时降低企业市场营销决策支持错误率和响应时间。