A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustab...A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.展开更多
The depth adjustment factor for bending strength stated in Eurocode 5(EC5)is only applicable to timbers having a characteristic density below 700 kg/m^(3).However,most Malaysian timbers are hardwood,some with a charac...The depth adjustment factor for bending strength stated in Eurocode 5(EC5)is only applicable to timbers having a characteristic density below 700 kg/m^(3).However,most Malaysian timbers are hardwood,some with a characteristic density reaching above 700 kg/m^(3).Therefore,the objective of this study was to examine whether the depth adjustment factor stipulated in EC5 is valid for Malaysian hardwood timbers.Six timber species were selected for this study,namely Kapur(Dryobalanops C.F.Gaertn.),Kempas(Koompassia Maingay ex Benth.),Keruing(Dipterocarpus C.F.Gaertn.),Light red meranti(Shorea Roxb.ex C.F.Gaertn.),Geronggang(Cratoxylum Blume)and Balau(Shorea Roxb.ex C.F.Gaertn.).The determination of bending strength and characteristic density was conducted according to BS EN 408:2010 and BS EN 384:2016,respectively.A graph for mean bending strength vs.(150/h)was plotted for each timber species.The power function was selected to analyze the relationship between the two variables.The power of the regression equations varied depending on the characteristic density of the timber species.For species with a characteristic density below 700 kg/m^(3),such as Kapur,Keruing,and Light red meranti,the power was between 0.16 to 0.17.In contrast,for species having a characteristic density above 700 kg/m^(3),namely Kempas and Balau,the power was higher at 0.23 and 0.24,respectively.Geronggang was an exception to this pattern.These values are close to the depth adjustment factor given in EC5,which is 0.2.Based on the results,it can be suggested that the adjustment factor of 0.2 is also applicable to Malaysian hardwood timbers with a characteristic density above 700 kg/m^(3).展开更多
In this paper, adjustment factors J and R put forward by professor Zhou Jiangwen are introduced and the nature of the adjustment factors and their role in evaluating adjustment structure is discussed and proved.
The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is tha...The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is that the methodology was established solely based on human-driven passenger cars(HDPC)and human-driven heavy vehicles(HDHV).Due to automated passenger cars(APCs),a new adjustment factor(fAV)might be expected.This study simulated traffic flows at different percentages of HDHVs and APCs to investigate the impacts of HDHVs and APCs on freeway capacity by analyzing their influence on fHV and fAV values.The simulation determined observed adjustment factors at different percentages of HDHVs and APCs(fobserved).The HCM formula was used to calculate(fHCM).Modifications to the HCM formula are proposed,and vehicle adjustment factors due to HDHVs and APCs were calculated(fproposed).Results showed that,in the presence of APCs,while fobserved and fHCM were statistically significantly different,fobserved and fproposed were statistically equal.Hence,this study recommends using the proposed formula when determining vehicle adjustment factors(fproposed)due to HDHVs and APCs in the traffic stream.展开更多
The photovoltaic(PV)output process is inherently complex,often disrupted by a multitude of meteoro-logical factors,while conventional detection methods at PV power stations prove inadequate,compromising prediction acc...The photovoltaic(PV)output process is inherently complex,often disrupted by a multitude of meteoro-logical factors,while conventional detection methods at PV power stations prove inadequate,compromising prediction accuracy.To address this challenge,this paper introduces a power prediction method that leverages modal switching(MS),weight factor adjustment(WFA),and parallel long short-term memory(PALSTM).Initially,historical PV power station data is categorized into distinct modes based on global horizontal irradiance and converted solar angles.Correlation analysis is then employed to evaluate the impact of various meteorological factors on PV power,selecting those with strong correlations for each specific mode.Subsequently,the weights of meteorological parameters are optimized and adjusted,and a PALSTM neural network is constructed,with its parallel modal parameters refined through training.Depending on the prediction time and input data mode characteristics,the appropriate mode channel is selected to forecast PV power station generation.Ultimately,the feasibility of this method is validated through an illustrative analysis of measured data from an Australian PV power station.Comparative test results underscore the method’s advantages,particularly in scenarios where existing detection methods are lacking and meteorological factors frequently fluctuate,demonstrating its superior prediction accuracy and stability.展开更多
1 Introduction Vegetation indices(VIs)derived from satellite observations are an essential source of information for operational monitoring of the Earth’s vegetation(Qu et al.,2018;Yan et al.,2008).However,soil backg...1 Introduction Vegetation indices(VIs)derived from satellite observations are an essential source of information for operational monitoring of the Earth’s vegetation(Qu et al.,2018;Yan et al.,2008).However,soil background dramatically affects the performances ofⅥs(Baret and Guyot,1991;Gilabert et al.,2002;Huete,1988;Qi et al,1994).展开更多
AIM:To investigate the role of psychological characteristics as risk factors for oesophageal adenocarcinoma(OAC),as well as the reflux-mediated precursor pathway.METHODS:An all-Ireland population-based case-control st...AIM:To investigate the role of psychological characteristics as risk factors for oesophageal adenocarcinoma(OAC),as well as the reflux-mediated precursor pathway.METHODS:An all-Ireland population-based case-control study recruited 230 reflux oesophagitis(RO),224 Barrett's oesophagus(BO) and 227 OAC patients and 260 controls.Each case/control group completed measures of stress,depression,self-efficacy,self-esteem,repression and social support.A comparative analysis was undertaken using polytomous logistic regression adjusted for potential confounders.RESULTS:Compared to controls,OAC patients were almost half as likely to report high stress levels over their lifetime(P = 0.010,OR 0.51;95%CI:0.29-0.90)and 36% less likely to report having experienced depression(OR 0.64;95%CI:0.42-0.98).RO patients reported significantly higher stress than controls particularly during middle-and senior-years(P for trends < 0.001).RO patients were 37% less likely to report having been highly emotionally repressed(OR 0.63;95%CI:0.41-0.95).All case groups(OAC,RO and BO) were more likely than controls to report having had substantial amounts of social support(OR 2.84;95%CI:1.63-4.97;OR 1.97;95%CI:1.13-3.44 and OR 1.83;95%CI:1.03-3.24,respectively).CONCLUSION:The improved psychological profile of OAC patients may be explained by response shift.The role of psychological factors in the development of OAC requires further investigation.展开更多
文摘A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on line fuzzy inference system, and the other is a conventional PID controller. In the fuzzy inference system, three adjustable factors x p, x i , and x d are introduced. Their functions are to further modify and optimize the result of the fuzzy inference so as to make the controller have the optimal control effect on a given object. The optimal values of these adjustable factors are determined based on the ITAE criterion and the Nelder and Mead′s flexible polyhedron search algorithm. This optimal fuzzy PID controller has been used to control the executive motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that this controller is very effective and can be widely used to control different kinds of objects and processes.
基金funded by Geran Penyelidikan Khas(GPK),(600-RMC/GPK 5/3(071/2020)).
文摘The depth adjustment factor for bending strength stated in Eurocode 5(EC5)is only applicable to timbers having a characteristic density below 700 kg/m^(3).However,most Malaysian timbers are hardwood,some with a characteristic density reaching above 700 kg/m^(3).Therefore,the objective of this study was to examine whether the depth adjustment factor stipulated in EC5 is valid for Malaysian hardwood timbers.Six timber species were selected for this study,namely Kapur(Dryobalanops C.F.Gaertn.),Kempas(Koompassia Maingay ex Benth.),Keruing(Dipterocarpus C.F.Gaertn.),Light red meranti(Shorea Roxb.ex C.F.Gaertn.),Geronggang(Cratoxylum Blume)and Balau(Shorea Roxb.ex C.F.Gaertn.).The determination of bending strength and characteristic density was conducted according to BS EN 408:2010 and BS EN 384:2016,respectively.A graph for mean bending strength vs.(150/h)was plotted for each timber species.The power function was selected to analyze the relationship between the two variables.The power of the regression equations varied depending on the characteristic density of the timber species.For species with a characteristic density below 700 kg/m^(3),such as Kapur,Keruing,and Light red meranti,the power was between 0.16 to 0.17.In contrast,for species having a characteristic density above 700 kg/m^(3),namely Kempas and Balau,the power was higher at 0.23 and 0.24,respectively.Geronggang was an exception to this pattern.These values are close to the depth adjustment factor given in EC5,which is 0.2.Based on the results,it can be suggested that the adjustment factor of 0.2 is also applicable to Malaysian hardwood timbers with a characteristic density above 700 kg/m^(3).
文摘In this paper, adjustment factors J and R put forward by professor Zhou Jiangwen are introduced and the nature of the adjustment factors and their role in evaluating adjustment structure is discussed and proved.
文摘The highway capacity manual(HCM)provides a formula to calculate the heavy vehicle adjustment factor(fHV)as a function of passenger car equivalent factors for the heavy vehicle(ET).However,a significant drawback is that the methodology was established solely based on human-driven passenger cars(HDPC)and human-driven heavy vehicles(HDHV).Due to automated passenger cars(APCs),a new adjustment factor(fAV)might be expected.This study simulated traffic flows at different percentages of HDHVs and APCs to investigate the impacts of HDHVs and APCs on freeway capacity by analyzing their influence on fHV and fAV values.The simulation determined observed adjustment factors at different percentages of HDHVs and APCs(fobserved).The HCM formula was used to calculate(fHCM).Modifications to the HCM formula are proposed,and vehicle adjustment factors due to HDHVs and APCs were calculated(fproposed).Results showed that,in the presence of APCs,while fobserved and fHCM were statistically significantly different,fobserved and fproposed were statistically equal.Hence,this study recommends using the proposed formula when determining vehicle adjustment factors(fproposed)due to HDHVs and APCs in the traffic stream.
基金This work was supported in part by the Natural Science Foundation of Henan Province,and the specific grant number is 232300420301the initial of author is P.L.,the URL to the sponsors’websites is https://kjt.henan.gov.cn/(accessed on 09 February 2025)And this work was also supported in part by the Fundamental Research Funds for the Universities of Henan Province,and the specific grant number is NSFRF220425,the initial of author is P.L.,the URL to sponsors websites is http://app.hnkjt.gov.cn/web/index.do(accessed on 09 February 2025).
文摘The photovoltaic(PV)output process is inherently complex,often disrupted by a multitude of meteoro-logical factors,while conventional detection methods at PV power stations prove inadequate,compromising prediction accuracy.To address this challenge,this paper introduces a power prediction method that leverages modal switching(MS),weight factor adjustment(WFA),and parallel long short-term memory(PALSTM).Initially,historical PV power station data is categorized into distinct modes based on global horizontal irradiance and converted solar angles.Correlation analysis is then employed to evaluate the impact of various meteorological factors on PV power,selecting those with strong correlations for each specific mode.Subsequently,the weights of meteorological parameters are optimized and adjusted,and a PALSTM neural network is constructed,with its parallel modal parameters refined through training.Depending on the prediction time and input data mode characteristics,the appropriate mode channel is selected to forecast PV power station generation.Ultimately,the feasibility of this method is validated through an illustrative analysis of measured data from an Australian PV power station.Comparative test results underscore the method’s advantages,particularly in scenarios where existing detection methods are lacking and meteorological factors frequently fluctuate,demonstrating its superior prediction accuracy and stability.
基金granted by Land Resources Evolution Mechanism and Sustainable Use in Global Black Soil Critical Zone(IGCP 665)Geochemical Survey of Land Quality in 1:25 Northeast China Black Soil(Grant No.DD20160316).
文摘1 Introduction Vegetation indices(VIs)derived from satellite observations are an essential source of information for operational monitoring of the Earth’s vegetation(Qu et al.,2018;Yan et al.,2008).However,soil background dramatically affects the performances ofⅥs(Baret and Guyot,1991;Gilabert et al.,2002;Huete,1988;Qi et al,1994).
文摘AIM:To investigate the role of psychological characteristics as risk factors for oesophageal adenocarcinoma(OAC),as well as the reflux-mediated precursor pathway.METHODS:An all-Ireland population-based case-control study recruited 230 reflux oesophagitis(RO),224 Barrett's oesophagus(BO) and 227 OAC patients and 260 controls.Each case/control group completed measures of stress,depression,self-efficacy,self-esteem,repression and social support.A comparative analysis was undertaken using polytomous logistic regression adjusted for potential confounders.RESULTS:Compared to controls,OAC patients were almost half as likely to report high stress levels over their lifetime(P = 0.010,OR 0.51;95%CI:0.29-0.90)and 36% less likely to report having experienced depression(OR 0.64;95%CI:0.42-0.98).RO patients reported significantly higher stress than controls particularly during middle-and senior-years(P for trends < 0.001).RO patients were 37% less likely to report having been highly emotionally repressed(OR 0.63;95%CI:0.41-0.95).All case groups(OAC,RO and BO) were more likely than controls to report having had substantial amounts of social support(OR 2.84;95%CI:1.63-4.97;OR 1.97;95%CI:1.13-3.44 and OR 1.83;95%CI:1.03-3.24,respectively).CONCLUSION:The improved psychological profile of OAC patients may be explained by response shift.The role of psychological factors in the development of OAC requires further investigation.
