Due to the complexity of ecological compensation standards and methods, some problems cannot be expected before compensation, but the evaluation of eco-compensation effect can feedback the implementation effect of eco...
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Due to the complexity of ecological compensation standards and methods, some problems cannot be expected before compensation, but the evaluation of eco-compensation effect can feedback the implementation effect of eco-compensation policies and provide reference for the improvement of eco-compensation policies. This paper constructed a comprehensive evaluation index system of eco-compensation, which covered social and economic development, pollution discharge and monitoring, and pollution treatment aspects. An eco-compensation comprehensive evaluation model was established, which consisted of the projection pursuit model (PP model) and the chaotic particle swarm optimization algorithm (CPSO algorithm). The Xiaohong River Basin in China was selected as a case study. Before and after the implementation of eco-compensation policy, the compensation effects in the four counties in the basin from 2008 to 2015 were evaluated. The results showed that through the implementation of the basin eco-compensation policies, the comprehensive indicators in the four counties showed an upward trend, which indicated that the eco-compensation of the basin had achieved certain effects. Among them, Xincai was the best, and could provide reference for other counties. The research results can provide new ideas and new methods for the evaluation of eco-compensation effects.
It is important to ensure the radiation safety of workers in nuclear facilities. The path-planning technology is one of the effective ways to reduce the radiation exposure to the workers in the radioactive environment...
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It is important to ensure the radiation safety of workers in nuclear facilities. The path-planning technology is one of the effective ways to reduce the radiation exposure to the workers in the radioactive environment of nuclear facilities. This work studies the path-planning technology in radioactive environment of nuclear facilities, and proposes an improved particleswarmoptimization (PSO) algorithm to solve the path-planning problems. To be specific, particleswarmoptimizationalgorithm is associated with chaos optimizationalgorithm, and new mathematical dose calculation models for the path-planning problem are built. Then, experimental simulation for 3 cases is carried out and the results are compared to those from traditional PSO method. In the first two cases, the average effective doses from the improved PSO method are similar to those from traditional PSO method, but its possibility that the effective dose value is too large becomes smaller. And this trend is more obvious in Case 3. Specifically, the effective dose value above 800 mu Sv is cut by 25% for the improved PSO method. Besides, the average effective dose decreases about 29 mu Sv in Case 3. Meanwhile, the overall convergence rate isn't affected. Hence, the proposed path-planning method in the radioactive environment of nuclear facilities is demonstrated to be effective through the experiments and analysis.
Research the Incident Vehicle Routing Problem with Soft Time-windows (IVRP-STW). Associated logistics scheduling problem with soft time windows using the logistic function optimization method to improve the chaotic pa...
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Research the Incident Vehicle Routing Problem with Soft Time-windows (IVRP-STW). Associated logistics scheduling problem with soft time windows using the logistic function optimization method to improve the chaoticparticlealgorithm, compared with the GA and the standard PSO algorithm. Simulation results show that such optimization method can effectively improve the global search of the particles in the particleswarm and the ability of local search is effective in resolving such problems.
In this paper,an effective optimize method based on adaptive PID neural network controller is *** particleswarmoptimization（CPSO） is introduced to initialize the parameters of neural network for improving the conv...
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ISBN:
(纸本)9781538629185
In this paper,an effective optimize method based on adaptive PID neural network controller is *** particleswarmoptimization（CPSO） is introduced to initialize the parameters of neural network for improving the convergent speed and preventing weights trapping into local *** order to realize the hardware platform of PID neural network controller and facilitate weight update algorithm,the nanoscale memristor is utilized to analog electronic ***,the stability of closed-loop system is further proved by Lyapunov *** on several comparative experiments on automatic voltage regulation system,the final results illustrate that the proposed controller can obtain better precision in a shorter time.
In this paper, a predictive control algorithm is presented based on Type-2 fuzzy model and chaoticparticleswarmoptimization (CPSO) algorithm: using the Type-2 T-S fuzzy model as predictive model, and using CPSO alg...
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ISBN:
(纸本)9789881563811
In this paper, a predictive control algorithm is presented based on Type-2 fuzzy model and chaoticparticleswarmoptimization (CPSO) algorithm: using the Type-2 T-S fuzzy model as predictive model, and using CPSO algorithm to solve the optimization index, so the predictive control can avoid complex gradient calculation and matrix inversion, and can quickly to search the optimal solution. Furthermore, in order to improve the effectiveness of Type-2 model, the modified G-K clustering method is applied to determine the clustering number c and clustering centers. For a numerical example, the simulation results show the effectiveness of the algorithm proposed in this paper.
The market-oriented reform of the electric power industry is a trend around the world, electricity price issues are the key problems in the power markets and how to price the special commodity-electricity is essential...
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ISBN:
(纸本)9781424487363
The market-oriented reform of the electric power industry is a trend around the world, electricity price issues are the key problems in the power markets and how to price the special commodity-electricity is essential for the smooth market operation. Accurate price forecasting provides crucial information for electricity market participants to make reasonable competing strategies, which is related to the position and benefit of the market participators. So using the relative historic data in predicting the future electricity price is a very meaningful work. With comprehensive considerations of the fluctuation rules and the various influencing factors on the forming of price in the power market, a short-term electricity price forecasting method based on the time series ARMAX model was chosen in this paper. Aimed to solve the problem with traditional method of parameter identification which is easy to fall into the local least values and has low identification precision, chaoticparticleswarmoptimization (CPSO) algorithm was proposed in this paper. Calculation example shows that this method can reflect the law of the development of the electricity price well and improve forecasting accuracy greatly.
The market-oriented reform of the electric power industry is a trend around the world, electricity price issues are the key problems in the power markets and how to price the special commodity-electricity is essential...
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The market-oriented reform of the electric power industry is a trend around the world, electricity price issues are the key problems in the power markets and how to price the special commodity-electricity is essential for the smooth market operation. Accurate price forecasting provides crucial information for electricity market participants to make reasonable competing strategies, which is related to the position and benefit of the market participators. So using the relative historic data in predicting the future electricity price is a very meaningful work. With comprehensive considerations of the fluctuation rules and the various influencing factors on the forming of price in the power market, a short-term electricity price forecasting method based on the time series ARMAX model was chosen in this paper. Aimed to solve the problem with traditional method of parameter identification which is easy to fall into the local least values and has low identification precision, chaoticparticleswarmoptimization (CPSO) algorithm was proposed in this paper. Calculation example shows that this method can reflect the law of the development of the electricity price well and improve forecasting accuracy greatly.
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