Matter-element Model Research Articles

Eutrophication Assessment Based on the Cloud Matter Element Model.

Eutrophication has become one of the most serious problems threatening the lakes/reservoirs in China over 50 years. Evaluation of eutrophication is a multi-criteria decision-making process with uncertainties. In this study, a cloud matter element (CME) model was developed in order to evaluate eutrophication level objectively and scientifically, which incorporated the randomness and fuzziness of eutrophication evaluation process. The elements belonging to each eutrophication level in the CME model were determined by means of certainty degrees through repeated simulations of cloud model with reasonable parameters of expectation Ex, entropy En, and hyper-entropy He. The weights of evaluation indicators were decided by a combination of entropy technology and analytic hierarchy process method. The neartudes of water samples to each eutrophication level of lakes/reservoirs in the CME model were generated and the eutrophication levels were determined by maximum neartude principal. The proposed CME model was applied to evaluate eutrophication levels of 24 typical lakes/reservoirs in China. The results of the CME model were compared with those of comprehensive index method, matter element model, fuzzy matter element model, and cloud model. Most of the results obtained by the CME model were consistent with the results obtained by other methods, which proved the CME model is an effective tool to evaluate eutrophication.

Evaluation of Bus Accessibility Based on Hotspot Detection and Matter-Element Analysis

The paper aims to assess bus accessibility considering the matching between supply and demand for effectively optimizing the level and fairness of urban public transport service, which realizes the quantification of regional balance and accurate positioning the area with the worst balance. We firstly employ hotspot detection procedure based on taxi trajectory data and kernel density analysis to identify the travel sensitive areas, the heat values of which are deployed to represent travel demand spatial-temporally and evaluate weight factors for bus accessibility modeling. Matter-element theory is selected to establish multi-parameter evaluation model of bus accessibility, which has potential for solving incompatibility problems by systematically considering all factors. The correlations between accessibility indexes and heat value are deployed to evaluate weight factors rather than analytic hierarchy process or expert assessment method to improve subjectivity and dynamic updating. An index called the Level Ratio of Accessibility to Demand ( LRAD ) is addressed finally to quantify the balance between accessibility supply and travel demand of travel sensitive areas, which identifies the regional imbalance to assist the public transport system assignment. Xi’an, a large city, is selected as a case study for methodology verification. Bus accessibility degree of the whole city as well as its travel sensitive areas is evaluated by the matter-element model. It is found the bus transport accessibility of Xi’an is moderate level $(M_{3})$ . The LRAD results identify the priority-processing area with the poor balance between accessibility supply and travel demand, which is cross referenced with local urban plans for verification.

基于熵权的模糊物元模型在河流健康评价中的应用研究

基于熵权的模糊物元模型在河流健康评价中的应用研究

Failure mode and effects analysis using extended matter-element model and AHP

Failure mode and effects analysis (FMEA) is a widely applied risk assessment method in engineering and management fields. In a typical FMEA, the ranking orders of failure modes are determined by risk priority number (RPN) which can be determined by multiplication of the scores of risk factors. However, the typical RPN has been criticized for several limitations when employed in practical situations. In this paper, a novel FMEA method using extended matter-element model and analytic hierarchy process (AHP) is developed to overcome the limitations of the typical RPN. The scores of failure modes with respect to risk factors are obtained according to the typical RPN method, and the weights among risk factors are derived from AHP. The extended matter-element model integrating with AHP is developed to calculate the closeness coefficients of failure modes, according to which the ranking orders of failure modes are determined. An illustrative example, which implements FMEA to evaluate an ocean fishing vessel, is presented to demonstrate the application and effectiveness of the proposed method. Finally, a sensitivity analysis is implemented to explore the influences of the weights of risk factors and a comparison analysis is carried out to show the advantages of the proposed method.

Risk Analysis and Extension Assessment for the Stability of Surrounding Rock in Deep Coal Roadway.

In order to evaluate the surrounding rock stability of deep roadways, the diversity of accident hazard sources in deep coal mining is statistically analyzed. To conduct an effective evaluation, first, the risk analysis of the factors affecting the rock mass accidents is carried out, and the comprehensive safety index system of rock accidents in deep mine roadway is established. Further, combining the theory of hazard sources with the extension method, a matter–element model for the risk assessment of rock mass accidents in deep roadway is established. Finally, the hazard sources for the surrounding rock stability of deep roadway in the E-Zhuang coal mine of Xinwen Ming area are evaluated. The results show that the risk grade of the surrounding rock for deep roadways in E-Zhuang coal mine is “B”, which is generally safe, the human factors and organizational management factors are relatively safe, and some suggestions for improvement are put forward.

Evaluation of Open-Pit Mine Security Risk Based on FAHP-Extenics Matter-Element Model

In order to timely find out the safety problems in the production process, in this study, we focused on the present safety situation of ChangShaoHao open-pit gold mine in Inner Mongolia and established the overall safety environment risk evaluation matter-element model based on the Fuzzy analytical hierarchy process (FAHP) and extenics theory. In addition, for the analysis, four criteria layer indexes, thirteen sub-criteria layer indexes, and thirty-one measure layer indexes were selected as the overall risk (target layer) evaluation object. The basic data were mainly acquired by the means of on-site investigation, data analysis of the engineering, expert questionnaire, etc., followed by calculating the correlation degree of the bottom indexes with respect to the four safety grades through the extenics theory, and combining with the index weight of other layers obtained by the FAHP method. Finally, the comprehensive evaluation result was worked out. The overall security level of the open-pit mine is II, indicating that the overall safety level of the open-pit mine is acceptable. Simultaneously, some serious risks on mine’s safety need to be observed. The evaluation result fitted under the practical situation of the engineering, providing a good decision-making basis for the safe production and management work of gold mine.

Agricultural Land Suitability of Production Space in the Taihang Mountains, China

The contradiction between the shortage of land for agriculture due to rapid expansion of industrialization and urbanization and increasing population pressure is projected to impose great threats to future food security. Agricultural land suitability evaluation is an effective approach to improve the utilization of land resources for crop production and thus enhance the capacity of food provision. In this study, we evaluated the land suitability for agriculture of the production space in the Taihang Mountains by three steps: establishing indicator system, determining weights for indicators, and constructing a fuzzy matter-element model to assess the grades of suitability. Results showed that the land suitability had a significant linear correlation with potential crop yields, indicating our evaluation was effective to predict crop production. The spatial pattern of land suitability for crop production demonstrated that land with higher suitability was generally located in piedmont plains and basins, while land with lower suitability was mostly situated in mountainous areas. The area of highly, moderately, marginally suitable and unsuitable land for agriculture was 32.13%, 28.58%, 37.49% and 1.80% of the production space, respectively. However, the correlation degree analysis indicated that the requirements of these four suitability grades were currently not satisfied but could be potentially fulfilled. In terms of indicator weights, soil properties were much more important than topography and location conditions to influence the grades of suitability. Among all indicators, slope, soil organic matter, soil texture and soil depth were the most influential factors, so slope farming prevention and organic fertilization were most likely to improve land suitability for agriculture. Compared the outputs of our land suitability evaluation model with the distribution of the existing croplands, we found that about 66.52% of marginally suitable and 54.55% of unsuitable land for agriculture were currently used for croplands. Therefore, de-farming policy should be implemented in areas of these two suitability grades. In contrast, cropland expansion was encouraged in the land that was highly or moderately suitable for agriculture. Our evaluation of agricultural land suitability is beneficial for future land use planning and decision-making in the Taihang Mountains.

Research on reliability comprehensive evaluation method of five‐axis CNC machine tools based on AHP and extension theory

Currently, some five-axis CNC machine tools have almost achieved the same advanced level of the western countries in terms of functionality and performance. However, the reliability of system is much lower than similar foreign products. The reliability has become one of bottlenecks to restrict the development of domestic CNC machine tools. At present, domestic reliability research of CNC machine tools developed rapidly, but the evaluation research is limited to a single indicator, lacking overall evaluation about it. To fully evaluate the reliability of five-axis CNC machine tools, the matter-element model of reliability evaluation is established with the application of matter-element in extension theory, and the reliability evaluation indices system is established comprehensively. The correlation functions are introduced to calculate the correlation degree, and the weights of each evaluation indices are determined by using AHP. The actual example and result on two types of domestic CNC machine tools show that the proposed method is effective, reasonable, and accurate in the process of reliability evaluation. The proposed methodology provides a detailed instruction for comprehensive reliability evaluation of CNC machine tools.

Classifying and Predicting Salinization Level in Arid Area Soil Using a Combination of Chua's Circuit and Fractional Order Sprott Chaotic System.

Soil salinization is very complex and its evolution is affected by numerous interacting factors produce strong non-linear characteristics. This is the first time fractional order chaos theory has been applied to soil salinization-level classification to decrease uncertainty in salinization assessment, solve fuzzy problems, and analyze the spectrum chaotic features in soil with different levels of salinization. In this study, typical saline soil spectrum data from different human interference areas in Fukang City (Xinjiang) and salt index test data from an indoor chemical analysis laboratory are used as the base information source. First, we explored the correlation between the spectrum reflectance features of soil with different levels of salinization and chaotic dynamic error and chaotic attractor. We discovered that the chaotic status error in the 0.6 order has the greatest change. The 0.6 order chaotic attractors are used to establish the extension matter-element model. The determination equation is built according to the correspondence between section domain and classic domain range to salinization level. Finally, the salt content from the chemical analysis is substituted into the discriminant equation in the extension matter-element model. Analysis found that the accuracy of the discriminant equation is higher. For areas with no human interference, the extension classification can successfully identify nine out of 10 prediction data, which is a 90% identification accuracy rate. For areas with human interference, the extension classification can successfully identify 10 out of 10 prediction data, which is a success rate of 100%. The innovation in this study is the building of a smart classification model that uses a fractional order chaotic system to inversely calculate soil salinization level. This model can accurately classify salinization level and its predictive results can be used to rapidly calculate the temporal and spatial distribution of salinization in arid area/desert soil.

Fuzzy matter-element model based on entropy weight Comprehensive evaluation ofatmospheric pollutant emission reduction potential in the port area

Based on the entropy weight and fuzzy matter-element model, the entropy weight method is used to determine the weight coefficient of the evaluation index. The matter element analysis and the calculated entropy weight are used to calculate Euclidean. The degree of proximity has established a fuzzy matter element evaluation model for the entropy weight of atmospheric pollutants in the port area, and completed a comprehensive evaluation of different emission sources in the port area, providing technical support for scientific and effective reduction of air pollutants in the port area.

Evaluating Agricultural Sustainability Based on the Water–Energy–Food Nexus in the Chenmengquan Irrigation District of China

Agriculture is one of the largest consumers of water and energy. This paper evaluated the agricultural sustainability of the Chenmengquan irrigation district of China based on the water–energy–food nexus. One objective weighting method and one subjective weighting method were integrated, based on game theory, and a matter–element model was constructed to evaluate agricultural sustainability for the research region. The sensitivity of each index to the evaluation class was also analyzed. The results showed that agricultural sustainability was moderate in 2006–2012 and high in 2012–2015. The indexes, which represent water-use efficiency and yield per unit area of crops, had higher sensitivities in the context of the present case study. The results also indicated that agricultural sustainability had a comparatively positive trend between 2012 and 2015, and that pesticide utilization was the most important issue for agricultural sustainability. The approach of using the combination of a weighting method, based upon game theory, and the use of the matter–element model provides a guide for the evaluation of agricultural sustainability.

Dynamic Optimization Classification Model for Submarine Tunnel Surrounding Rocks and Its Application in Engineering

Hou, F.-J.; Xie, X.-K.; Shi, S.-S.; Song, S.-G.; Bu, L.; Li, L-P., and Zhou, Z.-Q., 2019. Dynamic optimization classification model for submarine tunnel surrounding rocks and its application in engineering. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 311–315. Coconut Creek (Florida), ISSN 0749-0208.In order to make the classification of tunnel surrounding rocks more reasonable and accurate, a multi-index matter-element extension evaluation model was proposed for the advanced optimization classification of submarine tunnel surrounding rocks based on the extension evaluation method. Firstly, the rock mass integrity index Kv, Young's modulus E, the longitudinal wave velocity Vp, Poisson's ratio l, and groundwater W were selected as the evaluation indices. Secondly, the TSP detection technology was employed to collect quantitative indices. The main influencing factors, which were non-dimensional, were used to set up the matter-elements in order to make the evaluation indices comparable. Lastly, the matter-element extension evaluation model was applied to a submarine tunnel construction project in China and the evaluation results were compared against the excavation conditions on site.

Assessment of River Water Quality Based on an Improved Fuzzy Matter-Element Model.

In this paper, an improved fuzzy matter-element (IFME) method was proposed, which integrates the classical matter-element (ME) method, set pair analysis (SPA), and variable coefficient method (VCM). The method was applied to evaluate water quality of five monitor stations along Caoqiao River in Yixing city, Jiangsu Province, China. The levels of river water quality were determined according to fuzzy closeness degree. Compared with the traditional evaluation methods, the IFME method has several characteristics as follows: (i) weights were determined by the VCM method, which can reduce workload and overcome the adverse effects of abnormal values, (ii) membership degrees were defined by SPA, which can utilize monitored data more scientifically and comprehensively, and (iii) IFME is more suitable for seriously polluted rivers. Overall, these findings reinforce the notion that an integrated approach is essential for attaining scientific and objective assessment of river water quality.

Comprehensive evaluation of water-use efficiency in China’s Huai river basin using a cloud–compound fuzzy matter element–entropy combined model

We are facing the water shortage crisis. To realise sustainable development, we should improve water-use efficiency (WUE). In this study, a cloud–compound fuzzy matter element–entropy combined model was constructed to evaluate WUE. The Huai river basin (HRB) was selected as the study area. The cloud model was used to select some indices and build the comprehensive evaluation index system (CEIS), which included the overall, agricultural, industrial, domestic and environmental categories. The compound fuzzy matter element model was used to calculate the comprehensive indicators of WUE of the HRB and its regions. The weight of each index in the CEIS was determined using the entropy model. The results showed that WUE of the HRB had an upward trend on the whole because of the enhanced emphasis on water resources by the international and national governments. However, the regional difference was obvious. The WUE of Henan province was higher than that of Jiangsu province. The imbalance of regional WUE is an international problem. By analysing the difference among regions, research can provide a reference for the decision making of the water resources management department.

Risk assessment for construction of urban rail transit projects

Taken all factors into consideration regarding the uncertainties of urban rail transit projects construction and incompatibility of the assessment conclusion, this paper proposes a vague fuzzy matter-element model for the risk assessment by combining vague set and matter-element theory. The risk assessment index system is based on a Work Breakdown Structure (WBS) – Risk Breakdown Structure (RBS) risk identification matrix. Risk assessment indicators are features of the matter, and values of risk indicators are vague values; Correlation transformation is operated on optimal subordinate degree, and the weights of risk assessment indicators were defined by structure entropy weight method. The level of the risk matter evaluated was then determined, according to the principle of maximum proximity. At last, the practicability and effectiveness of the proposed model was verified by a case study.

Application of Extension Neural Network with Discrete Wavelet Transform and Parseval’s Theorem for Power Quality Analysis

The development of renewable energy and the increase of intermittent fluctuating loads have affected the power quality of power systems, and in the long run, damage the power equipment. In order to effectively analyze the quality of power signals, this paper proposes a method of signal feature capture and fault identification, as based on the extension neural network (ENN) algorithm combined with discrete wavelet transform (DWT) and Parseval’s theorem. First, the original power quality disturbance (PQD) transient signal was subjected to DWT, and its spectrum energy was calculated for each order of wavelet coefficients through Parseval’s theorem, in order to effectively intercept the eigenvalues of the original signal. Based on the features, the extension neural algorithm was used to establish a matter-element model of power quality disturbance identification. In addition, the correlation degree between the identification data and disturbance types was calculated to accurately identify the types of power failure. To verify the accuracy of the proposed method, five common power quality disturbances were analyzed, including voltage sag, voltage swell, power interruption, voltage flicker, and power harmonics. The results were then compared with those obtained from the back-propagation network (BPN), probabilistic neural network (PNN), extension method and a learning vector quantization network (LVQ). The results showed that the proposed method has shorter computation time (0.06 s), as well as higher identification accuracy at 99.62%, which is higher than the accuracy rates of the other four types.

Comprehensive Eutrophication Assessment Based on Fuzzy Matter Element Model and Monte Carlo-Triangular Fuzzy Numbers Approach.

Evaluating the eutrophication level of lakes with a single method alone is challenging since uncertain, fuzzy, and complex processes exist in eutrophication evaluations. The parameters selected for assessing eutrophication include chlorophyII-a, chemical oxygen demand, total phosphorus, total nitrogen, and clarity. Firstly, to deal with the uncertainties and fuzziness of data, triangular fuzzy numbers (TFN) were applied to describe the fuzziness of parameters. Secondly, to assess the eutrophication grade of lakes comprehensively, an improved fuzzy matter element (FME) approach was incorporated with TFNs with weights determined by combination of entropy method and analytic hierarchy process (AHP). In addition, the Monte Carlo (MC) approach was applied to easily simulate the arithmetic operations of eutrophication evaluation. The hybrid model of TFN, FME, and MC method is termed as the TFN–MC–FME model, which can provide more valuable information for decision makers. The developed model was applied to assess the eutrophication levels of 24 typical lakes in China. The evaluation indicators were expressed by TFNs input into the FME model to evaluate eutrophication grade. The results of MC simulation supplied quantitative information of possible intervals, the corresponding probabilities, as well as the comprehensive eutrophication levels. The eutrophication grades obtained for most lakes were identical to the results of the other three methods, which proved the correctness of the model. The presented methodology can be employed to process the data uncertainties and fuzziness by stochastically simulating their distribution characteristics, and obtain a better understanding of eutrophication levels. Moreover, the proposed model can also describe the trend of eutrophication development in lakes, and provide more valuable information for lake management authorities.

Hybrid model for water quality assessment in Bosten Lake of China

A hybrid method to comprehensively assess the water quality level was proposed by combining triangular fuzzy numbers, Monte Carlo approaches, and fuzzy matter element model, which can provide more meaningful information for the environmental protection agency. The model was applied to assessment of water quality in the Bosen Lake. The results implied that water quality level for the Bosten Lake is level III, and the water quality of sampling sites were S7 > S13 > S17 > S9 > S11 > S15 > S12 > S14 > S10 > S1 > S6 > S16 > S5 > S4 > S3 > S2 > S8. The methodology can be employed to deal with uncertainty and fuzzy data by stochastically simulating their distribution characteristics, and obtain a better understanding of water quality levels.

Social stability risk assessment of NIMBY major projects by OWA, matter-element, and cloud model

Social stability risk assessment of NIMBY major projects by OWA, matter-element, and cloud model

Ecological security evaluation based on entropy matter-element model: A case study of Kunming city, southwest China

Ecological security is important for social and economic sustainable development which needs stable resources and eco-environment support. In this study, we established an evaluation indicator system considering pressure and pressure-bearing to quantify the ecological security for Kunming city as it is a socioeconomic center in Southwest China with important ecological niche and rapid urbanization. According to the weights assigned by entropy method, we overlaid 13 indicators which were divided into 2 units, pressure indicators and pressure-bearing indicators, to evaluate the ecological security on grid scale. And then, ecological security level on district-county scale was evaluated based on the entropy matter-element model. On this basis, we explored their spatial distribution characteristics and the change trend from 2000 to 2015. Results showed that spatial distribution characteristic of ecological security evaluation was similar with the results of pressure evaluation, showing the scores and levels gradually increased from the urban area to the surrounding areas. Compared the ecological security levels in 2000 and in 2015, both of the highest value and the lowest value increased slightly. In general, the area with improved ecological security situation accounted for 89.10% of the total area. In terms of the change trend of ecological security levels, eight counties deteriorated while five counties remained unchanged which were driven by different deterioration reasons. The evaluation results of this study can provide comprehensive and targeted support for regional sustainable development.