Objective:Explore the characteristics of acupoints in the treatment of stroke with complex network and point mutual information method.Methods:The complex network and point wise mutual information system-developed by ...Objective:Explore the characteristics of acupoints in the treatment of stroke with complex network and point mutual information method.Methods:The complex network and point wise mutual information system-developed by Chinese academy of Chinese medical sciences wereused to analyze the specific acupoints,compatibility,frequency etc.Results:174 acumoxibustion prescriptions were collected,including 163 acupoints.among them eighteen acupoints were used more than 30 times such as Hegu(LI4),Zusanli(ST36),Quchi(LI11)and Fengshi(GB31).The combinations of 31 acupoints were used more than 15 times,such as the combination of Quchi(LI11)and Zusanli(ST36),the combination of acupoint Quchi(LI11)and Jianyu(LI15),Hegu and Quchi(LI11).The most commonly used treatment method for stroke treatment is to dredge the Yangming meridian and Shaoyang meridian through acupuncture the multiple acupoints located on these two meridians..The commonly used acupoints are mainly distributed in the limbs,head and face.The most commonly used specific acupoint is intersection acupoint.The usage frequency of specific acupoints are higher than that of non-specific acupoints.Conclusion:Dredging the collaterals,dispelling wind-evil and restoring consciousness are the main principle for the treatment of stroke.Specific acupoints in head,face and climbs maybe the main targeted acupoints.Combination of Yang meridians with other meridians is needed to improve the effects.The Yangming meridian and Shaoyang meridian are most used meridians and Hegu(LI4),Quchi(LI11)and Zusanli(ST36)are the most used acupionts.展开更多
The flash points of organic compounds were estimated using a hybrid method that includes a simple group contribution method (GCM) implemented in an artificial neural network (ANN) with particle swarm optimization (PSO...The flash points of organic compounds were estimated using a hybrid method that includes a simple group contribution method (GCM) implemented in an artificial neural network (ANN) with particle swarm optimization (PSO). Different topologies of a multilayer neural network were studied and the optimum architecture was determined. Property data of 350 compounds were used for training the network. To discriminate different substances the molecular structures defined by the concept of the classical group contribution method were given as input variables. The capabilities of the network were tested with 155 substances not considered in the training step. The study shows that the proposed GCM+ANN+PSO method represent an excellent alternative for the estimation of flash points of organic compounds with acceptable accuracy (AARD = 1.8%; AAE = 6.2 K).展开更多
Under the environment of electric power market, economic dispatch (ED) problem should consider network constraints, unit ramp rates, besides the basic constraints. For this problem, it is important to establish the ef...Under the environment of electric power market, economic dispatch (ED) problem should consider network constraints, unit ramp rates, besides the basic constraints. For this problem, it is important to establish the effective model and algorithm. This paper examines the decoupled conditions that affect the solution optimality to this problem. It proposes an effective model and solution method. Based on the look-ahead technique, it finds the number of time intervals to guarantee the solution optimality. Next, an efficient technique for finding the optimal solution via the interior point methods is described. Test cases, which include dispatching six units over 5 time intervals on the IEEE 30 test system with line flows and ramp constraints are presented. Results indicate that the computational effort as measured by iteration counts or execution time varies only modestly with the problem size.展开更多
为分析智能软开关(soft open point,SOP)连续调节能力对柔性配电网(flexible distribution network,FDN)风险的影响。首先,实现基于三点估计的FDN风险评估方法;采用三点估计法结合交直流交替迭代法和Gram-Charlier级数展开法进行FDN概...为分析智能软开关(soft open point,SOP)连续调节能力对柔性配电网(flexible distribution network,FDN)风险的影响。首先,实现基于三点估计的FDN风险评估方法;采用三点估计法结合交直流交替迭代法和Gram-Charlier级数展开法进行FDN概率潮流计算,获得节点电压与支路有功功率的概率密度函数,使用越限偏移量结合风险偏好型效用函数构建严重度函数,根据风险评估理论建立并计算风险评估指标。其次,在此基础上,提出一种计及SOP参数优化的FDN风险评估方法;以系统总风险最低为目标,建立计及SOP参数优化的FDN风险评估模型,采用粒子群优化算法结合基于三点估计的FDN风险评估方法对其进行求解,用得到的结果去配置SOP,并对此FDN进行风险评估。以3个IEEE 33节点网络通过三端口SOP互联形成的FDN为例,验证了所提风险评估方法的有效性,分析了SOP连续调节能力以及不同接入位置对FDN风险的影响。展开更多
Ground hydraulic fracturing plays a crucial role in controlling the far-field hard roof,making it imperative to identify the most suitable target stratum for effective control.Physical experiments are conducted based ...Ground hydraulic fracturing plays a crucial role in controlling the far-field hard roof,making it imperative to identify the most suitable target stratum for effective control.Physical experiments are conducted based on engineering properties to simulate the gradual collapse of the roof during longwall top coal caving(LTCC).A numerical model is established using the material point method(MPM)and the strain-softening damage constitutive model according to the structure of the physical model.Numerical simulations are conducted to analyze the LTCC process under different hard roofs for ground hydraulic fracturing.The results show that ground hydraulic fracturing releases the energy and stress of the target stratum,resulting in a substantial lag in the fracturing of the overburden before collapse occurs in the hydraulic fracturing stratum.Ground hydraulic fracturing of a low hard roof reduces the lag effect of hydraulic fractures,dissipates the energy consumed by the fracture of the hard roof,and reduces the abutment stress.Therefore,it is advisable to prioritize the selection of the lower hard roof as the target stratum.展开更多
Clustering approaches are one of the probabilistic load flow(PLF)methods in distribution networks that can be used to obtain output random variables,with much less computation burden and time than the Monte Carlo simu...Clustering approaches are one of the probabilistic load flow(PLF)methods in distribution networks that can be used to obtain output random variables,with much less computation burden and time than the Monte Carlo simulation(MCS)method.However,a challenge of the clustering methods is that the statistical characteristics of the output random variables are obtained with low accuracy.This paper presents a hybrid approach based on clustering and Point estimate methods.In the proposed approach,first,the sample points are clustered based on the𝑙-means method and the optimal agent of each cluster is determined.Then,for each member of the population of agents,the deterministic load flow calculations are performed,and the output variables are calculated.Afterward,a Point estimate-based PLF is performed and the mean and the standard deviation of the output variables are obtained.Finally,the statistical data of each output random variable are modified using the Point estimate method.The use of the proposed method makes it possible to obtain the statistical properties of output random variables such as mean,standard deviation and probabilistic functions,with high accuracy and without significantly increasing the burden of calculations.In order to confirm the consistency and efficiency of the proposed method,the 10-,33-,69-,85-,and 118-bus standard distribution networks have been simulated using coding in Python®programming language.In simulation studies,the results of the proposed method have been compared with the results obtained from the clustering method as well as the MCS method,as a criterion.展开更多
文摘Objective:Explore the characteristics of acupoints in the treatment of stroke with complex network and point mutual information method.Methods:The complex network and point wise mutual information system-developed by Chinese academy of Chinese medical sciences wereused to analyze the specific acupoints,compatibility,frequency etc.Results:174 acumoxibustion prescriptions were collected,including 163 acupoints.among them eighteen acupoints were used more than 30 times such as Hegu(LI4),Zusanli(ST36),Quchi(LI11)and Fengshi(GB31).The combinations of 31 acupoints were used more than 15 times,such as the combination of Quchi(LI11)and Zusanli(ST36),the combination of acupoint Quchi(LI11)and Jianyu(LI15),Hegu and Quchi(LI11).The most commonly used treatment method for stroke treatment is to dredge the Yangming meridian and Shaoyang meridian through acupuncture the multiple acupoints located on these two meridians..The commonly used acupoints are mainly distributed in the limbs,head and face.The most commonly used specific acupoint is intersection acupoint.The usage frequency of specific acupoints are higher than that of non-specific acupoints.Conclusion:Dredging the collaterals,dispelling wind-evil and restoring consciousness are the main principle for the treatment of stroke.Specific acupoints in head,face and climbs maybe the main targeted acupoints.Combination of Yang meridians with other meridians is needed to improve the effects.The Yangming meridian and Shaoyang meridian are most used meridians and Hegu(LI4),Quchi(LI11)and Zusanli(ST36)are the most used acupionts.
文摘The flash points of organic compounds were estimated using a hybrid method that includes a simple group contribution method (GCM) implemented in an artificial neural network (ANN) with particle swarm optimization (PSO). Different topologies of a multilayer neural network were studied and the optimum architecture was determined. Property data of 350 compounds were used for training the network. To discriminate different substances the molecular structures defined by the concept of the classical group contribution method were given as input variables. The capabilities of the network were tested with 155 substances not considered in the training step. The study shows that the proposed GCM+ANN+PSO method represent an excellent alternative for the estimation of flash points of organic compounds with acceptable accuracy (AARD = 1.8%; AAE = 6.2 K).
文摘Under the environment of electric power market, economic dispatch (ED) problem should consider network constraints, unit ramp rates, besides the basic constraints. For this problem, it is important to establish the effective model and algorithm. This paper examines the decoupled conditions that affect the solution optimality to this problem. It proposes an effective model and solution method. Based on the look-ahead technique, it finds the number of time intervals to guarantee the solution optimality. Next, an efficient technique for finding the optimal solution via the interior point methods is described. Test cases, which include dispatching six units over 5 time intervals on the IEEE 30 test system with line flows and ramp constraints are presented. Results indicate that the computational effort as measured by iteration counts or execution time varies only modestly with the problem size.
文摘为分析智能软开关(soft open point,SOP)连续调节能力对柔性配电网(flexible distribution network,FDN)风险的影响。首先,实现基于三点估计的FDN风险评估方法;采用三点估计法结合交直流交替迭代法和Gram-Charlier级数展开法进行FDN概率潮流计算,获得节点电压与支路有功功率的概率密度函数,使用越限偏移量结合风险偏好型效用函数构建严重度函数,根据风险评估理论建立并计算风险评估指标。其次,在此基础上,提出一种计及SOP参数优化的FDN风险评估方法;以系统总风险最低为目标,建立计及SOP参数优化的FDN风险评估模型,采用粒子群优化算法结合基于三点估计的FDN风险评估方法对其进行求解,用得到的结果去配置SOP,并对此FDN进行风险评估。以3个IEEE 33节点网络通过三端口SOP互联形成的FDN为例,验证了所提风险评估方法的有效性,分析了SOP连续调节能力以及不同接入位置对FDN风险的影响。
基金the National Natural Science Foundation of China(No.51974042)National Key Research and Development Program of China(No.2023YFC3009005).
文摘Ground hydraulic fracturing plays a crucial role in controlling the far-field hard roof,making it imperative to identify the most suitable target stratum for effective control.Physical experiments are conducted based on engineering properties to simulate the gradual collapse of the roof during longwall top coal caving(LTCC).A numerical model is established using the material point method(MPM)and the strain-softening damage constitutive model according to the structure of the physical model.Numerical simulations are conducted to analyze the LTCC process under different hard roofs for ground hydraulic fracturing.The results show that ground hydraulic fracturing releases the energy and stress of the target stratum,resulting in a substantial lag in the fracturing of the overburden before collapse occurs in the hydraulic fracturing stratum.Ground hydraulic fracturing of a low hard roof reduces the lag effect of hydraulic fractures,dissipates the energy consumed by the fracture of the hard roof,and reduces the abutment stress.Therefore,it is advisable to prioritize the selection of the lower hard roof as the target stratum.
文摘Clustering approaches are one of the probabilistic load flow(PLF)methods in distribution networks that can be used to obtain output random variables,with much less computation burden and time than the Monte Carlo simulation(MCS)method.However,a challenge of the clustering methods is that the statistical characteristics of the output random variables are obtained with low accuracy.This paper presents a hybrid approach based on clustering and Point estimate methods.In the proposed approach,first,the sample points are clustered based on the𝑙-means method and the optimal agent of each cluster is determined.Then,for each member of the population of agents,the deterministic load flow calculations are performed,and the output variables are calculated.Afterward,a Point estimate-based PLF is performed and the mean and the standard deviation of the output variables are obtained.Finally,the statistical data of each output random variable are modified using the Point estimate method.The use of the proposed method makes it possible to obtain the statistical properties of output random variables such as mean,standard deviation and probabilistic functions,with high accuracy and without significantly increasing the burden of calculations.In order to confirm the consistency and efficiency of the proposed method,the 10-,33-,69-,85-,and 118-bus standard distribution networks have been simulated using coding in Python®programming language.In simulation studies,the results of the proposed method have been compared with the results obtained from the clustering method as well as the MCS method,as a criterion.