During the desing of channel transect,the paper brings forward golden section method,which is 0.618 methods.In order to reduce the calculation volume of the natural depth of water h 0 and bottomˉwidth b which apply ...During the desing of channel transect,the paper brings forward golden section method,which is 0.618 methods.In order to reduce the calculation volume of the natural depth of water h 0 and bottomˉwidth b which apply trial calculation method and graphic method,and improve the calculate precision,the mathematical model has been built up,the writer combines example to explain the train of thought,the result shows that the calculation precision is high,the correctness is tested and verified by the result which is calculated by hand.It can be referred to the hydroelectric works.展开更多
To provide an energy-efficient and slab-demand-compliant rolling delay strategy,the simulation software is utilized to calculate the rolling delay process of the reheating furnace.Based on energy consumption evaluatio...To provide an energy-efficient and slab-demand-compliant rolling delay strategy,the simulation software is utilized to calculate the rolling delay process of the reheating furnace.Based on energy consumption evaluation,two optimization methods were employed.The bisection approach uses the needs of the slab to estimate the rolling delay temperature,and the golden section search method uses the energy consumption analysis of the slab to determine the high-temperature insulation duration.Generally,the slab closest to the discharge position in the control zone is selected as the optimization target.The optimized slab does not show a significant temperature rise after the end of the rolling delay process.When comparing the optimized rolling delay strategies with the traditional ones,the optimized rolling delay strategies not only meet the output requirements for slabs but also offer significant advantages in terms of energy efficiency,and this advantage increases with rolling delay time.展开更多
To determine proper flight parameters of an unmanned helicopter for tea plantation frost protection,field experiments were conducted to study the impact of flight height,speed and interval on airflow disturbance and t...To determine proper flight parameters of an unmanned helicopter for tea plantation frost protection,field experiments were conducted to study the impact of flight height,speed and interval on airflow disturbance and temperature rise around tea canopies based on the analysis and simulation of frost protection with a certain helicopter.The relationship between temperature rise after flight and the above flight parameters was established through a regression orthogonal experiment,based on which the optimal combination of flight parameters was obtained through the single-factor golden section method.The results showed that wind speed around tea canopies decreased with the increase of flight height when flight speed was constant.There was a multivariate linear relationship between temperature rise and flight parameters,and the sequence of flight parameters’influence on frost protection effect was flight interval,flight height,flight speed.The optimal combination of flight parameters were flight height of 4.0 m,flight speed of 6.0 m/s and flight interval of 20 min.After the flight with the above parameters air temperature around tea canopies increased 1.6℃ when background thermal inversion strength was 3.8℃.展开更多
The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy generation.To achieve safe management and optimal control of batteries,the state of ...The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy generation.To achieve safe management and optimal control of batteries,the state of charge(SOC)is one of the important parameters.The machine-learning based SOC estimation methods of lithium-ion batteries have attracted substantial interests in recent years.However,a common problem with these models is that their estimation performances are not always stable,which makes them difficult to use in practical applications.To address this problem,an optimized radial basis function neural network(RBF-NN)that combines the concepts of Golden Section Method(GSM)and Sparrow Search Algorithm(SSA)is proposed in this paper.Specifically,GSM is used to determine the optimum number of neurons in hidden layer of the RBF-NN model,and its parameters such as radial base center,connection weights and so on are optimized by SSA,which greatly improve the performance of RBF-NN in SOC estimation.In the experiments,data collected from different working conditions are used to demonstrate the accuracy and generalization ability of the proposed model,and the results of the experiment indicate that the maximum error of the proposed model is less than 2%.展开更多
文摘During the desing of channel transect,the paper brings forward golden section method,which is 0.618 methods.In order to reduce the calculation volume of the natural depth of water h 0 and bottomˉwidth b which apply trial calculation method and graphic method,and improve the calculate precision,the mathematical model has been built up,the writer combines example to explain the train of thought,the result shows that the calculation precision is high,the correctness is tested and verified by the result which is calculated by hand.It can be referred to the hydroelectric works.
文摘To provide an energy-efficient and slab-demand-compliant rolling delay strategy,the simulation software is utilized to calculate the rolling delay process of the reheating furnace.Based on energy consumption evaluation,two optimization methods were employed.The bisection approach uses the needs of the slab to estimate the rolling delay temperature,and the golden section search method uses the energy consumption analysis of the slab to determine the high-temperature insulation duration.Generally,the slab closest to the discharge position in the control zone is selected as the optimization target.The optimized slab does not show a significant temperature rise after the end of the rolling delay process.When comparing the optimized rolling delay strategies with the traditional ones,the optimized rolling delay strategies not only meet the output requirements for slabs but also offer significant advantages in terms of energy efficiency,and this advantage increases with rolling delay time.
基金The authors are grateful to the financial support by National High Technology Research and Development Program of China(2012AA10A508)National Natural Science Foundation of China(31101089)Priority Academic Program Development of Jiangsu Higher Education Institutions(2014-37)。
文摘To determine proper flight parameters of an unmanned helicopter for tea plantation frost protection,field experiments were conducted to study the impact of flight height,speed and interval on airflow disturbance and temperature rise around tea canopies based on the analysis and simulation of frost protection with a certain helicopter.The relationship between temperature rise after flight and the above flight parameters was established through a regression orthogonal experiment,based on which the optimal combination of flight parameters was obtained through the single-factor golden section method.The results showed that wind speed around tea canopies decreased with the increase of flight height when flight speed was constant.There was a multivariate linear relationship between temperature rise and flight parameters,and the sequence of flight parameters’influence on frost protection effect was flight interval,flight height,flight speed.The optimal combination of flight parameters were flight height of 4.0 m,flight speed of 6.0 m/s and flight interval of 20 min.After the flight with the above parameters air temperature around tea canopies increased 1.6℃ when background thermal inversion strength was 3.8℃.
基金This work was supported by the Fundamental Research Funds for the Central Universities(2022MS015)。
文摘The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy generation.To achieve safe management and optimal control of batteries,the state of charge(SOC)is one of the important parameters.The machine-learning based SOC estimation methods of lithium-ion batteries have attracted substantial interests in recent years.However,a common problem with these models is that their estimation performances are not always stable,which makes them difficult to use in practical applications.To address this problem,an optimized radial basis function neural network(RBF-NN)that combines the concepts of Golden Section Method(GSM)and Sparrow Search Algorithm(SSA)is proposed in this paper.Specifically,GSM is used to determine the optimum number of neurons in hidden layer of the RBF-NN model,and its parameters such as radial base center,connection weights and so on are optimized by SSA,which greatly improve the performance of RBF-NN in SOC estimation.In the experiments,data collected from different working conditions are used to demonstrate the accuracy and generalization ability of the proposed model,and the results of the experiment indicate that the maximum error of the proposed model is less than 2%.
