When analyze the uncertainty of the cost and the schedule of the spaceflight project, it is needed to know the value of the schedule-cost correlation coefficient. This paper deduces the schedule distribution, consider...When analyze the uncertainty of the cost and the schedule of the spaceflight project, it is needed to know the value of the schedule-cost correlation coefficient. This paper deduces the schedule distribution, considering the effect of the cost, and proposes the estimation formula of the correlation coefficient between the in（schedule） and the cost. On the basis of the fact and Taylor expansion, the relation expression between the schedule-cost correlation coefficient and the in-schedule-cost correlation coefficient is put forward. By analyzing the value features of the estimation formula of the in-schedule-cost correlation coefficient, the general rules are proposed to ascertain the value of the schedule-cost correlation coefficient. An example is given to demonstrate how to approximately amend the schedule-cost correlation coefficient based on the historical statistics, which reveals the traditional assigned value is inaccurate. The universality of this estimation method is analyzed.展开更多
To evaluate the cost risk and the schedule risk of the spaceflight project,the schedule-cost(S-C) correlation coefficient is directly appointed according to the experts' experience usually.This paper deduces SDMCU...To evaluate the cost risk and the schedule risk of the spaceflight project,the schedule-cost(S-C) correlation coefficient is directly appointed according to the experts' experience usually.This paper deduces SDMCU(the schedule distribution model considering the effect of the cost uncertainty),and then proposes the approximate formula to estimate the ln(S)-C correlation coefficient based on the models of SDMCU and CDMSU(the cost distribution model considering the effect of the schedule uncertainty).Furthermore,an approximate relationship expression of the S-C and the ln(S)-C correlation coefficients is put forward according to general facts and the Taylor expansion,and advanced by means of mass numerical validation is the general rule of obtaining the estimation value of the schedule-cost correlation coefficient based on the historical data.展开更多
Non-point source(NPS) pollution is considered to be one of the main threats of the aquatic environment. Mountainous regions are particularly important water sources for urban areas. The various driving factors of NPS ...Non-point source(NPS) pollution is considered to be one of the main threats of the aquatic environment. Mountainous regions are particularly important water sources for urban areas. The various driving factors of NPS pollution such as terrain, precipitation, and vegetation type in mountainous regions show clear spatial heterogeneity. Consequently, the management systems required for NPS pollution in mountainous regions are complex. In this study, we developed a framework to estimate and map the treatment costs for NPS pollution in mountainous regions and applied this method in Baoxing County, a typical mountainous county in Sichuan Province of southwest China. The export levels of total nitrogen(TN) and total phosphorus(TP) in Baoxing County were estimated using the water purification model in InVEST(Itegrated Valuation of Ecosystem Services and Tradeoffs) tool. NPS pollutant treatment costs were calculated based on the level of pollutants exports, water yield, water quality targets, and treatment costs of NPS pollutants per unit mass. The results show that at the watershed level the amounts of TN and TP exported in Baoxing County were below threshold limits. However, at the sub-watershed level, TN and TP excesses of 291.64 and 2.96 tons per year were found, respectively, with mean TN and TP treatment costs of 6.58 US$/hm^2 and 0.35 US$/hm^2. Appraising pollution treatment cost intuitively reflects the overall expenditure in NPS pollution reduction from an economic perspective. This study provides a foundation for the implementation of Payment for Ecosystem Service(PES) and the prevention and control of NPS pollution.展开更多
The values of non-marketable forest products have largely been ignored, which made the conservation of the natural resources increasingly more economically difficult. Based on the previous studies, compensation subsid...The values of non-marketable forest products have largely been ignored, which made the conservation of the natural resources increasingly more economically difficult. Based on the previous studies, compensation subsidy for the values of non-marketable forest products was computed with a method of compensation coefficient that combines the Engel Coefficient and Logistic Curve. The method was applied in Changbai Mountain area. The total value of the compensation subsidy in 1999 was supposed to 637.93 Yuan·hm-2, of which 70% would be paid directly to the local stakeholders and is much higher than the compensation subsidy previously computed (75Yuan·hm-2·year-1). It is currently impossible for the central government to bear all the costs and investment of natural forest protection. A practical solution is that the local government should invest in forest and put the compensation subsidy into the current revenue.展开更多
Economic Dispatch (ED) problem is one of the main concerns of the power generation operations which are basically solved to generate optimal amount of power from the generating units in the system by minimizing the fu...Economic Dispatch (ED) problem is one of the main concerns of the power generation operations which are basically solved to generate optimal amount of power from the generating units in the system by minimizing the fuel cost and by satisfying the system constraints. The accuracy of ED solutions is highly influenced by the fuel cost parameters of the generating units. Generally, the parameters are subjected to transform due to aging process and other external issues. Further the parameters associated with the transmission line modelling also change due to aforementioned issues. The loss coefficients which are the functions of transmission line parameters get altered from the original value over a time. Hence, the periodical estimation of these coefficients is highly essential in power system problems for obtaining ideal solutions for ED problem. Estimating the ideal parameters of the ED problem may be the best solution for this issue. This paper presents the Teaching Learning Based Optimization (TLBO) algorithm to estimate the parameters associated with ED problem. The estimation problem is formulated as an error minimization problem. This work provides a frame work for the computation of coefficients for quadratic function, piecewise quadratic cost function, emission function, transmission line parameters and loss coefficients. The effectiveness of TLBO is tested with 2 standard test systems and an Indian utility system.展开更多
An objective function model is proposed for cost in optimizing and allocating tolerance with consideration of manufacturing conditions. With the fuzzy comprehensive evaluation method,a manufacturing difficulty coeffic...An objective function model is proposed for cost in optimizing and allocating tolerance with consideration of manufacturing conditions. With the fuzzy comprehensive evaluation method,a manufacturing difficulty coefficient is derived,which takes into account of several factors affecting the manufacturing cost,including the forming means of the blank,size,machining surface features,operator’s skills and machinability of materials. The coefficient is then converted into a weight factor used in the inversed square model representing the relationship between the cost and tolerance,and,hence,an objective function for cost is established in optimizing and allocating tolerance. The higher is the manufacturing difficulty coefficient,the higher is the relative manufacturing cost and the higher is the weight factor of the tolerance allocation,which indicates the increase of the tolerance’s effects on the total manufacturing cost and,therefore,a larger tolerance should be allocated. The computer-aided tolerance allocation utilizing this model makes it more convenient,accurate and practicable.展开更多
In view of the difficulty in predicting the cost data of power transmission and transformation projects at present,a method based on Pearson correlation coefficient-improved particle swarm optimization(IPSO)-extreme l...In view of the difficulty in predicting the cost data of power transmission and transformation projects at present,a method based on Pearson correlation coefficient-improved particle swarm optimization(IPSO)-extreme learning machine(ELM)is proposed.In this paper,the Pearson correlation coefficient is used to screen out the main influencing factors as the input-independent variables of the ELM algorithm and IPSO based on a ladder-structure coding method is used to optimize the number of hidden-layer nodes,input weights and bias values of the ELM.Therefore,the prediction model for the cost data of power transmission and transformation projects based on the Pearson correlation coefficient-IPSO-ELM algorithm is constructed.Through the analysis of calculation examples,it is proved that the prediction accuracy of the proposed method is higher than that of other algorithms,which verifies the effectiveness of the model.展开更多
基金This project was supported by Weapon System Advanced Research Foundation(51419010204KG01) and National ScienceFoundation of China(70272002).
文摘When analyze the uncertainty of the cost and the schedule of the spaceflight project, it is needed to know the value of the schedule-cost correlation coefficient. This paper deduces the schedule distribution, considering the effect of the cost, and proposes the estimation formula of the correlation coefficient between the in（schedule） and the cost. On the basis of the fact and Taylor expansion, the relation expression between the schedule-cost correlation coefficient and the in-schedule-cost correlation coefficient is put forward. By analyzing the value features of the estimation formula of the in-schedule-cost correlation coefficient, the general rules are proposed to ascertain the value of the schedule-cost correlation coefficient. An example is given to demonstrate how to approximately amend the schedule-cost correlation coefficient based on the historical statistics, which reveals the traditional assigned value is inaccurate. The universality of this estimation method is analyzed.
文摘To evaluate the cost risk and the schedule risk of the spaceflight project,the schedule-cost(S-C) correlation coefficient is directly appointed according to the experts' experience usually.This paper deduces SDMCU(the schedule distribution model considering the effect of the cost uncertainty),and then proposes the approximate formula to estimate the ln(S)-C correlation coefficient based on the models of SDMCU and CDMSU(the cost distribution model considering the effect of the schedule uncertainty).Furthermore,an approximate relationship expression of the S-C and the ln(S)-C correlation coefficients is put forward according to general facts and the Taylor expansion,and advanced by means of mass numerical validation is the general rule of obtaining the estimation value of the schedule-cost correlation coefficient based on the historical data.
基金sponsored by National Natural Science Foundation of China (Grant Nos. 41371539)Guangxi Natural Science Foundation Program (Grant Nos. 2018GXNSFBA138026)Guangxi Young and Middle-aged University Teachers’ Scientific Research Ability Enhancement Project (Grant Nos. 2018KY0360)
文摘Non-point source(NPS) pollution is considered to be one of the main threats of the aquatic environment. Mountainous regions are particularly important water sources for urban areas. The various driving factors of NPS pollution such as terrain, precipitation, and vegetation type in mountainous regions show clear spatial heterogeneity. Consequently, the management systems required for NPS pollution in mountainous regions are complex. In this study, we developed a framework to estimate and map the treatment costs for NPS pollution in mountainous regions and applied this method in Baoxing County, a typical mountainous county in Sichuan Province of southwest China. The export levels of total nitrogen(TN) and total phosphorus(TP) in Baoxing County were estimated using the water purification model in InVEST(Itegrated Valuation of Ecosystem Services and Tradeoffs) tool. NPS pollutant treatment costs were calculated based on the level of pollutants exports, water yield, water quality targets, and treatment costs of NPS pollutants per unit mass. The results show that at the watershed level the amounts of TN and TP exported in Baoxing County were below threshold limits. However, at the sub-watershed level, TN and TP excesses of 291.64 and 2.96 tons per year were found, respectively, with mean TN and TP treatment costs of 6.58 US$/hm^2 and 0.35 US$/hm^2. Appraising pollution treatment cost intuitively reflects the overall expenditure in NPS pollution reduction from an economic perspective. This study provides a foundation for the implementation of Payment for Ecosystem Service(PES) and the prevention and control of NPS pollution.
文摘The values of non-marketable forest products have largely been ignored, which made the conservation of the natural resources increasingly more economically difficult. Based on the previous studies, compensation subsidy for the values of non-marketable forest products was computed with a method of compensation coefficient that combines the Engel Coefficient and Logistic Curve. The method was applied in Changbai Mountain area. The total value of the compensation subsidy in 1999 was supposed to 637.93 Yuan·hm-2, of which 70% would be paid directly to the local stakeholders and is much higher than the compensation subsidy previously computed (75Yuan·hm-2·year-1). It is currently impossible for the central government to bear all the costs and investment of natural forest protection. A practical solution is that the local government should invest in forest and put the compensation subsidy into the current revenue.
文摘Economic Dispatch (ED) problem is one of the main concerns of the power generation operations which are basically solved to generate optimal amount of power from the generating units in the system by minimizing the fuel cost and by satisfying the system constraints. The accuracy of ED solutions is highly influenced by the fuel cost parameters of the generating units. Generally, the parameters are subjected to transform due to aging process and other external issues. Further the parameters associated with the transmission line modelling also change due to aforementioned issues. The loss coefficients which are the functions of transmission line parameters get altered from the original value over a time. Hence, the periodical estimation of these coefficients is highly essential in power system problems for obtaining ideal solutions for ED problem. Estimating the ideal parameters of the ED problem may be the best solution for this issue. This paper presents the Teaching Learning Based Optimization (TLBO) algorithm to estimate the parameters associated with ED problem. The estimation problem is formulated as an error minimization problem. This work provides a frame work for the computation of coefficients for quadratic function, piecewise quadratic cost function, emission function, transmission line parameters and loss coefficients. The effectiveness of TLBO is tested with 2 standard test systems and an Indian utility system.
文摘An objective function model is proposed for cost in optimizing and allocating tolerance with consideration of manufacturing conditions. With the fuzzy comprehensive evaluation method,a manufacturing difficulty coefficient is derived,which takes into account of several factors affecting the manufacturing cost,including the forming means of the blank,size,machining surface features,operator’s skills and machinability of materials. The coefficient is then converted into a weight factor used in the inversed square model representing the relationship between the cost and tolerance,and,hence,an objective function for cost is established in optimizing and allocating tolerance. The higher is the manufacturing difficulty coefficient,the higher is the relative manufacturing cost and the higher is the weight factor of the tolerance allocation,which indicates the increase of the tolerance’s effects on the total manufacturing cost and,therefore,a larger tolerance should be allocated. The computer-aided tolerance allocation utilizing this model makes it more convenient,accurate and practicable.
文摘In view of the difficulty in predicting the cost data of power transmission and transformation projects at present,a method based on Pearson correlation coefficient-improved particle swarm optimization(IPSO)-extreme learning machine(ELM)is proposed.In this paper,the Pearson correlation coefficient is used to screen out the main influencing factors as the input-independent variables of the ELM algorithm and IPSO based on a ladder-structure coding method is used to optimize the number of hidden-layer nodes,input weights and bias values of the ELM.Therefore,the prediction model for the cost data of power transmission and transformation projects based on the Pearson correlation coefficient-IPSO-ELM algorithm is constructed.Through the analysis of calculation examples,it is proved that the prediction accuracy of the proposed method is higher than that of other algorithms,which verifies the effectiveness of the model.
