To improve the performance of fuel cells, the operating temperature of molten carbonate fuel cell (MCFC) stack should be controlled within a specified range. In this paper, with the RBF neural network’s ability of id...To improve the performance of fuel cells, the operating temperature of molten carbonate fuel cell (MCFC) stack should be controlled within a specified range. In this paper, with the RBF neural network’s ability of identifying complex nonlinear systems, a neural network identification model of MCFC stack is developed based on the sampled input-output data. Also, a novel online fuzzy control procedure for the temperature of MCFC stack is developed based on the fuzzy genetic algorithm (FGA). Parameters and rules of the fuzzy controller are optimized. With the neural network identification model, simulation of MCFC stack control is carried out. Validity of the model and the superior performance of the fuzzy controller are demonstrated.展开更多
A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-bes...A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-best S-D assignment. In the dynamic part of dataassociation, the results of the m-best S-D assignment are then used in turn, with a Kalman filterstate estimator, in a multi-population FGA-based dynamic 2D assignment algorithm to estimate thestates of the moving targets over time. Such an assignment-based data association algorithm isdemonstrated on a simulated passive sensor track formation and maintenance problem. The simulationresults show its feasibility in multi-sensor multi-target tracking. Moreover, algorithm developmentand real-time problems are briefly discussed.展开更多
目的探究血清可溶性CD14(sCD14)亚型(sCD14-ST,Presepsin)、肽聚糖识别蛋白2(PGLYRP2)、纤维蛋白原α链(fibrinogen alpha chain,FGA)在耐药结核病诊断中的潜在价值。方法收集2019年1月至2020年12月我院诊断为肺结核(PTB)且初治患者(≥1...目的探究血清可溶性CD14(sCD14)亚型(sCD14-ST,Presepsin)、肽聚糖识别蛋白2(PGLYRP2)、纤维蛋白原α链(fibrinogen alpha chain,FGA)在耐药结核病诊断中的潜在价值。方法收集2019年1月至2020年12月我院诊断为肺结核(PTB)且初治患者(≥18岁)416例的临床信息,包括患者的性别、年龄、职业、吸烟史等临床基本信息和痰培养阳性患者的固体培养结果。采用χ^(2)检验进行单因素分析,应用Logistic回归分析及绘制受试者工作特性(ROC)曲线分析曲线下面积。结果耐药组患者血清待检测标志物sCD14-ST[28.54(26.48,31.51)pg/mL vs 12.24(11.71,14.30)pg/mL]、PGLYRP2[554.70(390.29,764.95)pg/mL vs 158.45(106.37,219.72)pg/mL]、FGA[73.33(66.0,99.73)pg/mL vs 39.0(35.65,42.65)pg/mL]水平均高于敏感组(P<0.05)。经多因素Logistic回归分析,血清sCD14-ST、PGLYRP2、FGA都是影响PTB患者耐药性的独立危险因素(P<0.05)。经ROC曲线分析,血清sCD14-ST、PGLYRP2、FGA用于耐药PTB诊断的曲线下面积分别为0.975(0.960~0.990)、0.983(0.972~0.994)、0.959(0.936~0.983),cut-off值分别为17.85pg/mL、283.84pg/mL、47.80pg/mL,在该阈值下,灵敏度分别为98.2%、96.4%、96.4%,特异性分别为95.0%、90.3%、91.4%。结论血清标志物sCD14-ST、PGLYRP2、FGA在耐药PTB中有较高的诊断价值。展开更多
For data association in multisensor and multitarget tracking, a novel parallel algorithm is developed to improve the efficiency and real-time performance of FGAs-based algorithm. One Cluster of Workstation （COW） wit...For data association in multisensor and multitarget tracking, a novel parallel algorithm is developed to improve the efficiency and real-time performance of FGAs-based algorithm. One Cluster of Workstation （COW） with Message Passing Interface （MPI） is built. The proposed Multi-Deme Parallel FGA （MDPFGA） is run on the platform. A serial of special MDPFGAs are used to determine the static and the dynamic solutions of generalized m-best S-D assignment problem respectively, as well as target states estimation in track management. Such an assignment-based parallel algorithm is demonstrated on simulated passive sensor track formation and maintenance problem. While illustrating the feasibility of the proposed algorithm in multisensor multitarget tracking, simulation results indicate that the MDPFGAs-based algorithm has greater efficiency and speed than the FGAs-based algorithm.展开更多
文摘To improve the performance of fuel cells, the operating temperature of molten carbonate fuel cell (MCFC) stack should be controlled within a specified range. In this paper, with the RBF neural network’s ability of identifying complex nonlinear systems, a neural network identification model of MCFC stack is developed based on the sampled input-output data. Also, a novel online fuzzy control procedure for the temperature of MCFC stack is developed based on the fuzzy genetic algorithm (FGA). Parameters and rules of the fuzzy controller are optimized. With the neural network identification model, simulation of MCFC stack control is carried out. Validity of the model and the superior performance of the fuzzy controller are demonstrated.
文摘A novel data association algorithm is developed based on fuzzy geneticalgorithms (FGAs). The static part of data association uses one FGA to determine both the lists ofcomposite measurements and the solutions of m-best S-D assignment. In the dynamic part of dataassociation, the results of the m-best S-D assignment are then used in turn, with a Kalman filterstate estimator, in a multi-population FGA-based dynamic 2D assignment algorithm to estimate thestates of the moving targets over time. Such an assignment-based data association algorithm isdemonstrated on a simulated passive sensor track formation and maintenance problem. The simulationresults show its feasibility in multi-sensor multi-target tracking. Moreover, algorithm developmentand real-time problems are briefly discussed.
文摘目的探究血清可溶性CD14(sCD14)亚型(sCD14-ST,Presepsin)、肽聚糖识别蛋白2(PGLYRP2)、纤维蛋白原α链(fibrinogen alpha chain,FGA)在耐药结核病诊断中的潜在价值。方法收集2019年1月至2020年12月我院诊断为肺结核(PTB)且初治患者(≥18岁)416例的临床信息,包括患者的性别、年龄、职业、吸烟史等临床基本信息和痰培养阳性患者的固体培养结果。采用χ^(2)检验进行单因素分析,应用Logistic回归分析及绘制受试者工作特性(ROC)曲线分析曲线下面积。结果耐药组患者血清待检测标志物sCD14-ST[28.54(26.48,31.51)pg/mL vs 12.24(11.71,14.30)pg/mL]、PGLYRP2[554.70(390.29,764.95)pg/mL vs 158.45(106.37,219.72)pg/mL]、FGA[73.33(66.0,99.73)pg/mL vs 39.0(35.65,42.65)pg/mL]水平均高于敏感组(P<0.05)。经多因素Logistic回归分析,血清sCD14-ST、PGLYRP2、FGA都是影响PTB患者耐药性的独立危险因素(P<0.05)。经ROC曲线分析,血清sCD14-ST、PGLYRP2、FGA用于耐药PTB诊断的曲线下面积分别为0.975(0.960~0.990)、0.983(0.972~0.994)、0.959(0.936~0.983),cut-off值分别为17.85pg/mL、283.84pg/mL、47.80pg/mL,在该阈值下,灵敏度分别为98.2%、96.4%、96.4%,特异性分别为95.0%、90.3%、91.4%。结论血清标志物sCD14-ST、PGLYRP2、FGA在耐药PTB中有较高的诊断价值。
基金Supported by National Defence Scientific Research Foundation
文摘For data association in multisensor and multitarget tracking, a novel parallel algorithm is developed to improve the efficiency and real-time performance of FGAs-based algorithm. One Cluster of Workstation （COW） with Message Passing Interface （MPI） is built. The proposed Multi-Deme Parallel FGA （MDPFGA） is run on the platform. A serial of special MDPFGAs are used to determine the static and the dynamic solutions of generalized m-best S-D assignment problem respectively, as well as target states estimation in track management. Such an assignment-based parallel algorithm is demonstrated on simulated passive sensor track formation and maintenance problem. While illustrating the feasibility of the proposed algorithm in multisensor multitarget tracking, simulation results indicate that the MDPFGAs-based algorithm has greater efficiency and speed than the FGAs-based algorithm.
