Subjects: Statistics >> Applied Statistical Mathematics Subjects: Computer Science >> Computer Application Technology Subjects: Mathematics >> Modeling and Simulation Subjects: Energy Science >> Energy Science （General） submitted time 2024-01-01
Abstract： The surging demand for new energy vehicles is propelled by the call to conserve energy, curtail emissions, and enhance the ecological ambience. By conducting behavioral analysis and mining, particular usage patterns of new en#2;ergy vehicles are pinpointed. Regrettably, these models decrease their environ#2;mental shielding efficiency. For instance, overloading the battery, operating with low battery power, and driving at excessive speeds can all detrimentally affect the battery's performance. To assess the impact of such driving behavior on the urban ecology, an environmental computational modeling method has been pro#2;posed to simulate the interaction between new energy vehicles and the environ#2;ment. To extend the time series data of the vehicle's entire life cycle and the eco#2;logical environment within the model sequence data, I utilized the LSTM deep learning method with Bayesian optimizer optimization parameters for longer simulation. The analysis revealed the detrimental effects of poor driving behavior on the environment
Peer Review Status:
Awaiting Review
Subjects: Mathematics >> Modeling and Simulation submitted time 2021-05-07
Abstract： In recent years, Grey system theory has been widely used in various fields. Among the Grey Prediction Models, the GM (1,1) model is the core and foundation. However, due to the exponential time response sequence, GM (1,1) model is difficult to simulate the oscillation sequence, and the oscillation sequence can not pass the GM (1,1) pre modeling test. These factors weaken the application of GM (1,1) model. The paper establishes GM (1,1) model for the 1-AGO sequence of oscillation sequence, by using the advantage of monotone sequence simulation of GM (1,1) model. Then, the IAGO operation with correction term is introduced to restore the simulation of oscillation sequence. Finally, an improved GM (1,1) model is established to make up for the defect of the traditional GM (1,1) model in the simulation of oscillation sequence.
Peer Review Status:Awaiting Review
Subjects: Mathematics >> Modeling and Simulation submitted time 2021-04-23
Abstract： Grey system model is widely used in mathematical modeling and approximate calculation because of its simplicity and clear mathematical background. The principle of grey system model can be summarized as the use of time response function to simulate the evolution of data series. Among them, GM (1,1) model is the most basic and can reflect the idea of grey modeling most widely. The time response function of the traditional GM (1,1) model is constructed by the exponent of natural constant . Also, for this characteristic, the GM (1,1) model has strong limitations. In practical application, people often modify the time response function of GM (1,1) model. One of the most important correction methods is to couple the original time response function with other functions that can describe the properties of data series. For example, for data series with certain periodicity or quasi periodicity, the original time response function can be coupled with trigonometric function to form GM (1,1) - trigonometric function coupling model. In this paper, the feasibility of this model is deeply discussed, and the estimation method of the parameters in the time response function of the coupled model and the error analysis are proposed.
Peer Review Status:Awaiting Review
Subjects: Mathematics >> Modeling and Simulation Subjects: Biology >> Biomathematics submitted time 2020-02-25
Abstract： Here we report the analysis of epidemic data from Jan. 20th to Feb. 16th, 2020 in 24 provinces in China, whose total infected cases are larger than 100 till 02/16/2020, as well as 16 cities in Hubei province (the most severely affected area) except Shennongjia, based on dynamical models and automatical algorithms for parameter optimization. We forecast the COVID-19 epidemics in most provinces in China will end up soon before February 29th, while those for Hubei province (except Wuhan city) will be closed by the middle of March. The epidemic in Wuhan will continue to the beginning of April. And we suggest further close attentions should be paid to six provides, including Heilongjiang, Hebei, Jiangxi, Anhui, Guizhou and Sichuan, as well as six different cities, including Wuhan, Jingzhou, Ezhou, Suizhou, Tianmen and Enshi, in Hubei province. Moreover, it is hinted that clustering infection might be happened in Tianjin, Hebei, Chongqing, Sichuan, Hainan and Guangxi provides, and many cities inside Hubei province during the spreading of COVID-19, which needs further validation by epidemiological investigations in the future.
Peer Review Status:Awaiting Review
Subjects: Mathematics >> Modeling and Simulation submitted time 2019-10-23
Abstract： Radiation symmetry evaluation is critical to the laser driven Inertial Confinement Fusion (ICF), which is usually done by solving a view-factor equation model. The model is nonlinear, and the number of equations can be very large when the size of discrete mesh element is very small to achieve a prescribed accuracy, which may lead to an intensive equation solving process. In this paper, an efficient radiation symmetry analysis approach based on sparse representation is presented, in which, 1) the Spherical harmonics, annular Zernike polynomials and Legendre-Fourier polynomials are employed to sparsely represent the radiation flux on the capsule and cylindrical cavity, and the nonlinear energy equilibrium equations are transformed into the equations with sparse coefficients, which means there are many redundant equations, 2) only a few equations are selected to recover such sparse coefficients with Latin hypercube sampling, 3) a Conjugate Gradient Subspace Thresholding Pursuit (CGSTP) algorithm is then given to rapidly obtain such sparse coefficients equation with as few iterations as possible. Finally, the proposed method is validated with two experiment targets for Shenguang II and Shenguang III laser facility in China. The results show that only one tenth of computation time is required to solve one tenth of equations to achieve the radiation flux with comparable accuracy. Further more, the solution is much more efficient as the size of discrete mesh element decreases, in which, only 1.2% computation time is required to obtain the accurate result.
Peer Review Status:Awaiting Review
Subjects: Mathematics >> Modeling and Simulation submitted time 2017-05-25
Abstract：Millions of people benefit form Traditional Chinese Medicine TCM every day. Unfortunately till now TCM has not been accepted as science by world especially western people. Bian Zheng Lun Zhi is distillation of TCM. Syndrome is key in system of Bian Zheng Lun Zhi. Study about the syndrome is core of study of basic theory of TCM. We creatively interpret TCM through a view of cognitive science and take syndromes of TCM as concepts of brain. This paper try to introduce syndrome to western people in order to let western people understand our viewpoints more easily the best method is to adopt a manner that is easily understood by them already exists and has been thought to be right. So we employ neural network presented by foreign people as brain model instead of network presented by us Using two classic case of TCM we successfully clarify the three main properties of syndrome in TCM.
Peer Review Status:Awaiting Review
Hits
Hits
Downloads
Comment