Underwater multi-target tracking logic and decision (UMTLD) has difficulty resolving multi-target tracking problems for underwater vehicles. Present methods assume factors in UMTLD are uncorrelated, when these are a...Underwater multi-target tracking logic and decision (UMTLD) has difficulty resolving multi-target tracking problems for underwater vehicles. Present methods assume factors in UMTLD are uncorrelated, when these are actually in a complex, interdependent relationship. To provide this, an index set of multi-target tracking decision characteristics and an analytic network process (ANP) model of the UMTLD method was -established. This method brings the index set of multi-target tracking decision into the ANP model, and the optimization multitarket tracking decision is achieved via computation of the resulting supermatrix. The rationality and robustness of decision results increase in simulations by 13% and 47% respectively with analytic hierarchy process (AHP). These results indicate that the ANP method should be the preferred method when UMTLD factors are interdependent.展开更多
Due to the increasingly serious environmental pollution and destruction,especially humans' unreasonable activities,the ecological and economic system(EES) issues of Northwest region in China have attracted more an...Due to the increasingly serious environmental pollution and destruction,especially humans' unreasonable activities,the ecological and economic system(EES) issues of Northwest region in China have attracted more and more attention of the researchers.Aiming at evaluating its ecological and economic system health,a multi-objective evaluation framework called PressureState-Response(PSR) was established to describe the ecological and economic health situations.Meanwhile,an integrative set pair model combining set pair analysis(SPA) and fuzzy analytic hierarchy process(FAHP) was proposed to assess the ecological and economic system.Then the EES status of five northwest provinces(Shanxi,Gansu,Qinghai,Ningxia and Xinjiang) of Northwest region in China was evaluated during 1985 to 2009.The EES development trends of five provinces are obtained.In general,the health values of five provinces showed a rising trend.The health values of five provinces grew rapidly during 1985 to 2000.After 2000,the health values of five provinces still followed the present growth trend,but the growth is relatively smooth.The results show that the method proposed is effective for assessing the health of ecological and economic system.展开更多
The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. The...The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II (strength Pareto evolutionary algorithm II). We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR (near-infrared spectroscopy) spectrometry where the objective is the determination of a variable subgroup with information about E protein content (%), test weight (Kg/HI), WKT (wheat kernel texture) (%) and farinograph water absorption (%). The results of traditional techniques of multivariate calibration as the SPA (successive projections algorithm), PLS (partial least square) and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.展开更多
基金Supported by the State Key Laboratory Foundation under Grant No.9140C2304080607the Aviation Science Foundation under Grant No.05F53027
文摘Underwater multi-target tracking logic and decision (UMTLD) has difficulty resolving multi-target tracking problems for underwater vehicles. Present methods assume factors in UMTLD are uncorrelated, when these are actually in a complex, interdependent relationship. To provide this, an index set of multi-target tracking decision characteristics and an analytic network process (ANP) model of the UMTLD method was -established. This method brings the index set of multi-target tracking decision into the ANP model, and the optimization multitarket tracking decision is achieved via computation of the resulting supermatrix. The rationality and robustness of decision results increase in simulations by 13% and 47% respectively with analytic hierarchy process (AHP). These results indicate that the ANP method should be the preferred method when UMTLD factors are interdependent.
基金supported in partially by the National Society Science Fund of China(Grant No.09CJY020)the Special Fund of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,China(Grant No. 2011585312)+1 种基金the Fundamental Research Funds for the Central Universities of Hohai University2010 Jiangsu Province Qing Lan Project
文摘Due to the increasingly serious environmental pollution and destruction,especially humans' unreasonable activities,the ecological and economic system(EES) issues of Northwest region in China have attracted more and more attention of the researchers.Aiming at evaluating its ecological and economic system health,a multi-objective evaluation framework called PressureState-Response(PSR) was established to describe the ecological and economic health situations.Meanwhile,an integrative set pair model combining set pair analysis(SPA) and fuzzy analytic hierarchy process(FAHP) was proposed to assess the ecological and economic system.Then the EES status of five northwest provinces(Shanxi,Gansu,Qinghai,Ningxia and Xinjiang) of Northwest region in China was evaluated during 1985 to 2009.The EES development trends of five provinces are obtained.In general,the health values of five provinces showed a rising trend.The health values of five provinces grew rapidly during 1985 to 2000.After 2000,the health values of five provinces still followed the present growth trend,but the growth is relatively smooth.The results show that the method proposed is effective for assessing the health of ecological and economic system.
文摘The multiple determination tasks of chemical properties are a classical problem in analytical chemistry. The major problem is concerned in to find the best subset of variables that better represents the compounds. These variables are obtained by a spectrophotometer device. This device measures hundreds of correlated variables related with physicocbemical properties and that can be used to estimate the component of interest. The problem is the selection of a subset of informative and uncorrelated variables that help the minimization of prediction error. Classical algorithms select a subset of variables for each compound considered. In this work we propose the use of the SPEA-II (strength Pareto evolutionary algorithm II). We would like to show that the variable selection algorithm can selected just one subset used for multiple determinations using multiple linear regressions. For the case study is used wheat data obtained by NIR (near-infrared spectroscopy) spectrometry where the objective is the determination of a variable subgroup with information about E protein content (%), test weight (Kg/HI), WKT (wheat kernel texture) (%) and farinograph water absorption (%). The results of traditional techniques of multivariate calibration as the SPA (successive projections algorithm), PLS (partial least square) and mono-objective genetic algorithm are presents for comparisons. For NIR spectral analysis of protein concentration on wheat, the number of variables selected from 775 spectral variables was reduced for just 10 in the SPEA-II algorithm. The prediction error decreased from 0.2 in the classical methods to 0.09 in proposed approach, a reduction of 37%. The model using variables selected by SPEA-II had better prediction performance than classical algorithms and full-spectrum partial least-squares.