One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must ...One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.展开更多
A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded ...A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.展开更多
The indicators of flood damage assessment in the flood classification are often incompatible, and it is very difficult to use those indicators value directly for classification assessment. Projection pursuit technolog...The indicators of flood damage assessment in the flood classification are often incompatible, and it is very difficult to use those indicators value directly for classification assessment. Projection pursuit technology can project higher dimensional incompatible data into lower dimensional sub-space, and find the projection values for optimal projection index function to get the higher dimensional data structure features, which has been improved to be reasonable and effective for flood disaster classification assessment. However, it is a bit difficult to optimize the parameters of projection index functions, as a result, that limits the applications of this method. As an emerging heuristic global optimization algorithm based on swarm intelligence, particle swarm optimization algorithm has the ability of solving complex optimization problem, but it still be easily convergent early, and can not search the global optimal solution. In this paper, a flood disaster classification assessment method based on multi-swarm cooperative particle swarm optimization is proposed, which adopts a tri-parameter Logistic curve to construct the flood disaster projection pursuit model, and uses mul-ti-swarm system particle swarm optimization method to optimize the parameters of the projection index functions. The typical test function experiment shows that this optimization method can solve the early convergence commonly found in standard particle swarm optimization algorithm, which global optimized ability is improved greatly. Applied in flood disaster assessment in HeNan Province, the results using this method comparing with others indicates that it can assess effectively the flood disaster, and has better assessment accuracy and disaster resolution.展开更多
Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by using projection pursuit model. The larger the projection value is,the better the model. Thus,according to the ...Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by using projection pursuit model. The larger the projection value is,the better the model. Thus,according to the projection value,the best one can be chosen from the model aggregation. Because projection pursuit modeling based on accelerating genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.展开更多
In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is ...In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation： to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.展开更多
The water quality of main rivers in Binzhou City,Shandong Province was comprehensively evaluated based on RAGA-PPCE model. Six main factors such as ammonia nitrogen(NH-N),total phosphorus(TP),total nitrogen(TN),chemic...The water quality of main rivers in Binzhou City,Shandong Province was comprehensively evaluated based on RAGA-PPCE model. Six main factors such as ammonia nitrogen(NH-N),total phosphorus(TP),total nitrogen(TN),chemical oxygen demand(COD),dissolved oxygen(DO) and p H were used to establish the evaluation and classification standards of water quality. The results show that the evaluation results of water quality by RAGA-PPCE model and the fuzzy comprehensive evaluation method are basically the same. The evaluation results of RAGA-PPCE model are objective and reasonable and can be applied to the comprehensive evaluation of water quality.展开更多
文摘One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.
基金Project supported by the China Postdoctoral Science Foundation,the Youth Foundation of Sichuan University(No.432028)and the National High-Tech Research and Development Program of China(863 Program)(No.2002AA2Z4251).
文摘A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.
文摘The indicators of flood damage assessment in the flood classification are often incompatible, and it is very difficult to use those indicators value directly for classification assessment. Projection pursuit technology can project higher dimensional incompatible data into lower dimensional sub-space, and find the projection values for optimal projection index function to get the higher dimensional data structure features, which has been improved to be reasonable and effective for flood disaster classification assessment. However, it is a bit difficult to optimize the parameters of projection index functions, as a result, that limits the applications of this method. As an emerging heuristic global optimization algorithm based on swarm intelligence, particle swarm optimization algorithm has the ability of solving complex optimization problem, but it still be easily convergent early, and can not search the global optimal solution. In this paper, a flood disaster classification assessment method based on multi-swarm cooperative particle swarm optimization is proposed, which adopts a tri-parameter Logistic curve to construct the flood disaster projection pursuit model, and uses mul-ti-swarm system particle swarm optimization method to optimize the parameters of the projection index functions. The typical test function experiment shows that this optimization method can solve the early convergence commonly found in standard particle swarm optimization algorithm, which global optimized ability is improved greatly. Applied in flood disaster assessment in HeNan Province, the results using this method comparing with others indicates that it can assess effectively the flood disaster, and has better assessment accuracy and disaster resolution.
基金The Key Project of NSFC(No.70631003)the Liberal Arts and Social Science Programming Project of Chinese Ministry of Education(No.07JA790109)
文摘Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by using projection pursuit model. The larger the projection value is,the better the model. Thus,according to the projection value,the best one can be chosen from the model aggregation. Because projection pursuit modeling based on accelerating genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.
文摘In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation： to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.
基金Supported by the Project of Humanities and Social Sciences in Shandong Province,China(18-ZZ-JJ-01)Key Project of Social Sciences in Binzhou City(18-SKGH-02)Action Plan for Servicing Binzhou of Binzhou University(BZXYSFW201719,BZXYSFW201713)
文摘The water quality of main rivers in Binzhou City,Shandong Province was comprehensively evaluated based on RAGA-PPCE model. Six main factors such as ammonia nitrogen(NH-N),total phosphorus(TP),total nitrogen(TN),chemical oxygen demand(COD),dissolved oxygen(DO) and p H were used to establish the evaluation and classification standards of water quality. The results show that the evaluation results of water quality by RAGA-PPCE model and the fuzzy comprehensive evaluation method are basically the same. The evaluation results of RAGA-PPCE model are objective and reasonable and can be applied to the comprehensive evaluation of water quality.
