Based on the fundamental principles of total amount control of water use, the harmony theory was used in this study to develop a concept of the degree of harmony of total amount control of water use. Based on this con...Based on the fundamental principles of total amount control of water use, the harmony theory was used in this study to develop a concept of the degree of harmony of total amount control of water use. Based on this concept, the harmoniousness of total amount control of water use was analyzed in terms of the supply and demand of water resources, water resources management, water use benefits, and water-saving level. An evaluation index system of the degree of harmony of total amount control of water use was established, and a method for calculation of the degree of harmony of total amount control of water use was developed based on the analytic hierarchy process （AHP） and fuzzy comprehensive analysis （FCA） methods. The new evaluation index system was applied to a certain area in Jiangsu Province, China. The degree of harmony of total amount control of water use over this area was calculated for different years. Results indicate that the evaluation index system and calculation method proposed in this study are feasible, and such a harmoniousness analysis can provide scientific references for the strict water resources management system that will be implemented in China in the near future.展开更多
The danger degree evaluation of coal and gas outburst is mainly evaluating spot risk using the safety examination table and the evaluation value can be found.Ac- cording to factors influence coal and gas outburst majo...The danger degree evaluation of coal and gas outburst is mainly evaluating spot risk using the safety examination table and the evaluation value can be found.Ac- cording to factors influence coal and gas outburst majorth were qualitative or fuzzy similar factors,used fuzzy gathering classification method for the coal and the gas outburst anal- ysis,established fuzzy model,according to the model adopted the fuzzy similar selective principle proceeding evaluated.Two kinds methods join together analysis can raise on the accuracy rate of the prediction.展开更多
The furnace process is very important in boiler operation,and furnace pressure works as an important parameter in furnace process.Therefore,there is a need to analyze and monitor the pressure signal in furnace.However...The furnace process is very important in boiler operation,and furnace pressure works as an important parameter in furnace process.Therefore,there is a need to analyze and monitor the pressure signal in furnace.However,little work has been conducted on the relationship with the pressure sequence and boiler’s load under different working conditions.Since pressure sequence contains complex information,it demands feature extraction methods from multi-aspect consideration.In this paper,fuzzy c-means analysis method based on weighted validity index(VFCM)has been proposed for the working condition classification based on feature extraction.To deal with the fluctuating and time-varying pressure sequence,feature extraction is taken as nonlinear analysis based on entropy theory.Three kinds of entropy values,extracted from pressure sequence in time-frequency domain,are studied as the clustering objects for work condition classification.Weighted validity index,taking the close and separation degree into consideration,is calculated on the base of Silhouette index and Krzanowski-Lai index to obtain the optimal clustering number.Each time FCM runs,the weighted validity index evaluates the clustering result and the optimal clustering number will be obtained when it reaches the maximum value.Four datasets from UCI Machine Learning Repository are presented to certify the effectiveness in VFCM.Pressure sequences got from a 300 MW boiler are then taken for case study.The result of the pressure sequence case study with an error rate of 0.5332%shows the valuable information on boiler’s load and pressure sequence in furnace.The relationship between boiler’s load and entropy values extracted from pressure sequence is proposed.Moreover,the method can be considered to be a reference method for data mining in other fluctuating and time-varying sequences.展开更多
文摘Based on the fundamental principles of total amount control of water use, the harmony theory was used in this study to develop a concept of the degree of harmony of total amount control of water use. Based on this concept, the harmoniousness of total amount control of water use was analyzed in terms of the supply and demand of water resources, water resources management, water use benefits, and water-saving level. An evaluation index system of the degree of harmony of total amount control of water use was established, and a method for calculation of the degree of harmony of total amount control of water use was developed based on the analytic hierarchy process （AHP） and fuzzy comprehensive analysis （FCA） methods. The new evaluation index system was applied to a certain area in Jiangsu Province, China. The degree of harmony of total amount control of water use over this area was calculated for different years. Results indicate that the evaluation index system and calculation method proposed in this study are feasible, and such a harmoniousness analysis can provide scientific references for the strict water resources management system that will be implemented in China in the near future.
基金the National Natural Science Foundation of China(50674052)
文摘The danger degree evaluation of coal and gas outburst is mainly evaluating spot risk using the safety examination table and the evaluation value can be found.Ac- cording to factors influence coal and gas outburst majorth were qualitative or fuzzy similar factors,used fuzzy gathering classification method for the coal and the gas outburst anal- ysis,established fuzzy model,according to the model adopted the fuzzy similar selective principle proceeding evaluated.Two kinds methods join together analysis can raise on the accuracy rate of the prediction.
基金supported by the National Natural Science Foundation of China(Grant No.51176030)Jiangsu Science and Technology Department(Grant No.BY2015070-17)
文摘The furnace process is very important in boiler operation,and furnace pressure works as an important parameter in furnace process.Therefore,there is a need to analyze and monitor the pressure signal in furnace.However,little work has been conducted on the relationship with the pressure sequence and boiler’s load under different working conditions.Since pressure sequence contains complex information,it demands feature extraction methods from multi-aspect consideration.In this paper,fuzzy c-means analysis method based on weighted validity index(VFCM)has been proposed for the working condition classification based on feature extraction.To deal with the fluctuating and time-varying pressure sequence,feature extraction is taken as nonlinear analysis based on entropy theory.Three kinds of entropy values,extracted from pressure sequence in time-frequency domain,are studied as the clustering objects for work condition classification.Weighted validity index,taking the close and separation degree into consideration,is calculated on the base of Silhouette index and Krzanowski-Lai index to obtain the optimal clustering number.Each time FCM runs,the weighted validity index evaluates the clustering result and the optimal clustering number will be obtained when it reaches the maximum value.Four datasets from UCI Machine Learning Repository are presented to certify the effectiveness in VFCM.Pressure sequences got from a 300 MW boiler are then taken for case study.The result of the pressure sequence case study with an error rate of 0.5332%shows the valuable information on boiler’s load and pressure sequence in furnace.The relationship between boiler’s load and entropy values extracted from pressure sequence is proposed.Moreover,the method can be considered to be a reference method for data mining in other fluctuating and time-varying sequences.
