The prediction process often runs with small samples and under-sufficient information.To target this problem,we propose a performance comparison study that combines prediction and optimization algorithms based on expe...The prediction process often runs with small samples and under-sufficient information.To target this problem,we propose a performance comparison study that combines prediction and optimization algorithms based on experimental data analysis.Through a large number of prediction and optimization experiments,the accuracy and stability of the prediction method and the correction ability of the optimization method are studied.First,five traditional single-item prediction methods are used to process small samples with under-sufficient information,and the standard deviation method is used to assign weights on the five methods for combined forecasting.The accuracy of the prediction results is ranked.The mean and variance of the rankings reflect the accuracy and stability of the prediction method.Second,the error elimination prediction optimization method is proposed.To make,the prediction results are corrected by error elimination optimization method(EEOM),Markov optimization and two-layer optimization separately to obtain more accurate prediction results.The degree improvement and decline are used to reflect the correction ability of the optimization method.The results show that the accuracy and stability of combined prediction are the best in the prediction methods,and the correction ability of error elimination optimization is the best in the optimization methods.The combination of the two methods can well solve the problem of prediction with small samples and under-sufficient information.Finally,the accuracy of the combination of the combined prediction and the error elimination optimization is verified by predicting the number of unsafe events in civil aviation in a certain year.展开更多
Considering the fluid flow non-darcy characteristics in fracture-vug carbonate reservoirs, a new multi-scale conduit flow model production prediction method for fracture-vug carbonate reservoirs was presented using im...Considering the fluid flow non-darcy characteristics in fracture-vug carbonate reservoirs, a new multi-scale conduit flow model production prediction method for fracture-vug carbonate reservoirs was presented using image segmentation technique of electric imaging logging data. Firstly, based on Hagen-Poiseuille's law of incompressible fluid flow and the different cross-sectional areas in single fractures and vugs in carbonate reservoirs, a multi-scale conduit flow model for fracture-vug carbonate reservoir was established, and a multi-scale conduit radial fluid flow equation was deduced. Then, conduit flow production index was introduced. The conduit flow production index was calculated using fracture-vug area extracted from the result of electrical image segmentation. Finally, production prediction of fracture-vug carbonate reservoir was realized by using electric imaging logging data. The method has been applied to Ordovician fracture-vug carbonate reservoirs in the Tabei area, and the predicted results are in good agreement with the oil testing data.展开更多
For wired local area networks(LANs),their effectiveness and invulnerability are very critical.It is extraordinarily significant to evaluate the network performance effectively in the design of a reasonable network top...For wired local area networks(LANs),their effectiveness and invulnerability are very critical.It is extraordinarily significant to evaluate the network performance effectively in the design of a reasonable network topology and the performance improvement of the networks.However,there are many factors affecting the performance of the networks,and the relation among them is also complicated.How to evaluate the performance of the wired LANs more accurately has been a heavy challenge in the network research.In order to solve the problem,this paper presents a performance evaluation method that evaluates the effectiveness and invulnerability of the wired LANs.Compared to traditional statistical methods,it has the distinct advantage of being able to handle several dependent variables simultaneously and tolerates the measurement errors among these independent variables and dependent variables.Finally,the rationality and validity of this method are verified by the extensive experimental simulation.展开更多
目的研究维持性血液透析(maintenance hemodialysis,MHD)患者血浆致动脉硬化指数(atherogenic index of plasma,AIP)、淋巴细胞与单核细胞比值(lymphocyte/monocyte ratio,LMR)与腹主动脉钙化(abdominal aortic calcification,AAC)的相...目的研究维持性血液透析(maintenance hemodialysis,MHD)患者血浆致动脉硬化指数(atherogenic index of plasma,AIP)、淋巴细胞与单核细胞比值(lymphocyte/monocyte ratio,LMR)与腹主动脉钙化(abdominal aortic calcification,AAC)的相关性,并构建风险预测模型。方法选取2023年5月1日─2024年4月30日在首都医科大学附属北京潞河医院郎府院区血液净化中心接受MHD治疗的患者。通过单因素及多因素Logistic回归分析来确定ACC的危险因素,建立列线图,并进行内部验证。结果共纳入158例MHD患者,分为AAC组(n=106)和非AAC组(n=52);AAC组的年龄(F=1.325,P<0.001)、校正钙(F=0.343,P=0.016)、AIP(F=8.726,P=0.003)、合并糖尿病(F=9.287,P=0.002)高于非AAC组;透析时长(F=3.681,P=0.007)、血白蛋白(F=3.287,P=0.002)、血磷(F=0.344,P=0.018)、LMR(F=1.824,P=0.022)低于非AAC组。多因素Logistic回归分析发现高龄(OR=1.071,95%CI:1.034~1.108,P<0.001)、合并糖尿病(OR=3.346,95%CI:1.428~7.843,P=0.005)、高AIP(OR=1.176,95%CI:1.041~1.33,P=0.009)、低LMR(OR=0.777,95%CI:0.614~0.983,P=0.036)是MHD患者发生AAC的独立危险因素。绘制列线图,计算C-index为0.834(95%CI:0.769~0.899),说明该列线图模型的区分能力较好。绘制校准曲线,模拟曲线和实际曲线绝对误差为0.029,说明模型具有较强的一致性。结论对于MHD患者来说,高龄、合并糖尿病、高AIP、低LMR是MHD患者发生AAC的独立危险因素。依据年龄、糖尿病、AIP、LMR构建的风险预测模型有很好的预测效能。展开更多
To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclai...To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclaiming effector is designed according to the operating characteristics.Firstly,the kinematics and singularity of the mechanism are analyzed.A multi-domain polar coordinate search method is proposed to obtain the workspace and the volume of the mechanism.Secondly,the dynamic modeling is completed and the example simulation is carried out.Thirdly,the motion-force transmission index of the mechanism is established.And based on the global transmissibility and the good-transmission workspace,the dimensional synthesis of the driving mechanism is completed by using the performance atlas-based method.Finally,aiming at the regular workspace size,stiffness and loading capacity,the Pareto optimal solution set of the executive mechanism dimension is obtained by using the multi-objective particle swarm optimization(MOPSO)algorithm.This paper can provide a theoretical basis for the optimal design and control of FG reclaiming robot.展开更多
A model of three-level amplified spontaneous emission(ASE)sources,considering radiation effect,is proposed to predict radiation induced loss of output power in radiation environment.Radiation absorption parameters of ...A model of three-level amplified spontaneous emission(ASE)sources,considering radiation effect,is proposed to predict radiation induced loss of output power in radiation environment.Radiation absorption parameters of ASE sources model are obtained by the fitting of color centers generation and recovery process of gain loss data at lower dose rate.Gain loss data at higher dose is applied for self-validating.This model takes both the influence of erbium ions absorption and photon bleaching effect into consideration,which makes the prediction of different dose and dose rate more accurate and flexible.The fitness value between ASE model and gain loss data is 99.98%,which also satisfies the extrapolation at the low dose rate.The method and model may serve as a valuable tool to predict ASE performance in harsh environment.展开更多
基金This work was supported by the Scientific Research Projects of Tianjin Educational Committee(No.2020KJ029)。
文摘The prediction process often runs with small samples and under-sufficient information.To target this problem,we propose a performance comparison study that combines prediction and optimization algorithms based on experimental data analysis.Through a large number of prediction and optimization experiments,the accuracy and stability of the prediction method and the correction ability of the optimization method are studied.First,five traditional single-item prediction methods are used to process small samples with under-sufficient information,and the standard deviation method is used to assign weights on the five methods for combined forecasting.The accuracy of the prediction results is ranked.The mean and variance of the rankings reflect the accuracy and stability of the prediction method.Second,the error elimination prediction optimization method is proposed.To make,the prediction results are corrected by error elimination optimization method(EEOM),Markov optimization and two-layer optimization separately to obtain more accurate prediction results.The degree improvement and decline are used to reflect the correction ability of the optimization method.The results show that the accuracy and stability of combined prediction are the best in the prediction methods,and the correction ability of error elimination optimization is the best in the optimization methods.The combination of the two methods can well solve the problem of prediction with small samples and under-sufficient information.Finally,the accuracy of the combination of the combined prediction and the error elimination optimization is verified by predicting the number of unsafe events in civil aviation in a certain year.
基金Supported by the China National Science and Technology Major Project(2011ZX05020-008)
文摘Considering the fluid flow non-darcy characteristics in fracture-vug carbonate reservoirs, a new multi-scale conduit flow model production prediction method for fracture-vug carbonate reservoirs was presented using image segmentation technique of electric imaging logging data. Firstly, based on Hagen-Poiseuille's law of incompressible fluid flow and the different cross-sectional areas in single fractures and vugs in carbonate reservoirs, a multi-scale conduit flow model for fracture-vug carbonate reservoir was established, and a multi-scale conduit radial fluid flow equation was deduced. Then, conduit flow production index was introduced. The conduit flow production index was calculated using fracture-vug area extracted from the result of electrical image segmentation. Finally, production prediction of fracture-vug carbonate reservoir was realized by using electric imaging logging data. The method has been applied to Ordovician fracture-vug carbonate reservoirs in the Tabei area, and the predicted results are in good agreement with the oil testing data.
基金supported by the National Natural Science Foundations of China (Nos.61572435,61472305, 61473222)the Ningbo Natural Science Foundations(Nos. 2016A610035,2017A610119)+1 种基金the Complex Electronic System Simulation Laboratory (No.DXZT-JC-ZZ-2015015)the Joint Fund of China State Shipbuilding Corporation(No.6141B03010103)
文摘For wired local area networks(LANs),their effectiveness and invulnerability are very critical.It is extraordinarily significant to evaluate the network performance effectively in the design of a reasonable network topology and the performance improvement of the networks.However,there are many factors affecting the performance of the networks,and the relation among them is also complicated.How to evaluate the performance of the wired LANs more accurately has been a heavy challenge in the network research.In order to solve the problem,this paper presents a performance evaluation method that evaluates the effectiveness and invulnerability of the wired LANs.Compared to traditional statistical methods,it has the distinct advantage of being able to handle several dependent variables simultaneously and tolerates the measurement errors among these independent variables and dependent variables.Finally,the rationality and validity of this method are verified by the extensive experimental simulation.
文摘目的研究维持性血液透析(maintenance hemodialysis,MHD)患者血浆致动脉硬化指数(atherogenic index of plasma,AIP)、淋巴细胞与单核细胞比值(lymphocyte/monocyte ratio,LMR)与腹主动脉钙化(abdominal aortic calcification,AAC)的相关性,并构建风险预测模型。方法选取2023年5月1日─2024年4月30日在首都医科大学附属北京潞河医院郎府院区血液净化中心接受MHD治疗的患者。通过单因素及多因素Logistic回归分析来确定ACC的危险因素,建立列线图,并进行内部验证。结果共纳入158例MHD患者,分为AAC组(n=106)和非AAC组(n=52);AAC组的年龄(F=1.325,P<0.001)、校正钙(F=0.343,P=0.016)、AIP(F=8.726,P=0.003)、合并糖尿病(F=9.287,P=0.002)高于非AAC组;透析时长(F=3.681,P=0.007)、血白蛋白(F=3.287,P=0.002)、血磷(F=0.344,P=0.018)、LMR(F=1.824,P=0.022)低于非AAC组。多因素Logistic回归分析发现高龄(OR=1.071,95%CI:1.034~1.108,P<0.001)、合并糖尿病(OR=3.346,95%CI:1.428~7.843,P=0.005)、高AIP(OR=1.176,95%CI:1.041~1.33,P=0.009)、低LMR(OR=0.777,95%CI:0.614~0.983,P=0.036)是MHD患者发生AAC的独立危险因素。绘制列线图,计算C-index为0.834(95%CI:0.769~0.899),说明该列线图模型的区分能力较好。绘制校准曲线,模拟曲线和实际曲线绝对误差为0.029,说明模型具有较强的一致性。结论对于MHD患者来说,高龄、合并糖尿病、高AIP、低LMR是MHD患者发生AAC的独立危险因素。依据年龄、糖尿病、AIP、LMR构建的风险预测模型有很好的预测效能。
基金supported by the National Natural Science Foundation of China(No.51905367)。
文摘To improve the operation situation of difficulty and low efficiency in the extraction of fermented grains(FG),a high-load and large-workspace reclaiming robot for ceramic cylinder fermentation is designed,and a reclaiming effector is designed according to the operating characteristics.Firstly,the kinematics and singularity of the mechanism are analyzed.A multi-domain polar coordinate search method is proposed to obtain the workspace and the volume of the mechanism.Secondly,the dynamic modeling is completed and the example simulation is carried out.Thirdly,the motion-force transmission index of the mechanism is established.And based on the global transmissibility and the good-transmission workspace,the dimensional synthesis of the driving mechanism is completed by using the performance atlas-based method.Finally,aiming at the regular workspace size,stiffness and loading capacity,the Pareto optimal solution set of the executive mechanism dimension is obtained by using the multi-objective particle swarm optimization(MOPSO)algorithm.This paper can provide a theoretical basis for the optimal design and control of FG reclaiming robot.
基金supported by the Aeronautical Science Foundation of China(Grant No.20170851007)。
文摘A model of three-level amplified spontaneous emission(ASE)sources,considering radiation effect,is proposed to predict radiation induced loss of output power in radiation environment.Radiation absorption parameters of ASE sources model are obtained by the fitting of color centers generation and recovery process of gain loss data at lower dose rate.Gain loss data at higher dose is applied for self-validating.This model takes both the influence of erbium ions absorption and photon bleaching effect into consideration,which makes the prediction of different dose and dose rate more accurate and flexible.The fitness value between ASE model and gain loss data is 99.98%,which also satisfies the extrapolation at the low dose rate.The method and model may serve as a valuable tool to predict ASE performance in harsh environment.
