Photovoltaic power system is taking a significant percentage of power system and the demands for accurate forecasting of the power outputs is surging. In prior works, the forecasting problem was formulated as a regression problem, however, which most cannot guarantee that the forecasted outputs is nonnegative. To solve this problem, we proposed a novel probabilistic model by using nonlinear regression and Bayesian learning method. In the paper, we present the detailed theoretical derivations and interpretations. The simulation results show the validity and feasibility of the proposed algorithm by comparing with the traditional SVM algorithm.
How to reduce the hardware cost and high power consumption of RF link of communication device is the key problem to be solved for multi-transmitting antenna and multi-receiving antenna system (MIMO). Always choose the best antennas connection a limited number of RF circuits, which is called antenna selection technology (AS), are a perfect solution to the problem, Assuming that the spatial range of the antenna meets the requirements of signal multiplexing and based on the maximum capacity criterion of the selected MIMO system, the manuscript proposes a low computational complexity (CC) and high performance joint transmitting and receiving antenna selection technique (JTRAS). Starting from the traditional capacity formula and the full matrix of MIMO channel, we utilize a simplified channel capacity expression through repeatedly iterating to delete a row and a column of the equivalent decrement channel matrix, which is to remove a pair of transmitting and receiving antennas. Based on the decreasing JTRAS (DJTRAS) algorithm, the capacity results of simulating calculation indicate that its median capacity overtakes other ones, such as optimum selection (OS), AS based on Frobenius 2 norm (NBS), and concise joint AS criterion (CJAS) etc., and the novel DJTRAS scheme can significantly reduce computational complexity (CC) compared to the exhaustive search method with maximum capacity, which defined as optimal algorithm in the curve graphs. This new technology of the AS is particularly suited to large number of selected antennas, such as Lt ≥ NT/2,Lr ≥ NR/2.
The mathematical algorithm of zero order optimization is a general function approach optimization method. Based on this method, many sets of analytical procedures are developed using ANSYS to study the design of 600m scale concrete arch bridge and the optimal arch axis coefficient, change mode and cross section sizes are obtained and verified. Results show: the mathematical algorithm of zero order optimization can effectively study the design of 600m arch bridge. The rich conclusions about design parameters can be a significant reference for design and further research of 600 m scale concrete arch bridge.
This paper studies Inventory location routing problem in supply chain distribution network planning under vendor inventory management while considering customer inventory holding cost. In order to minimize the total cost of supply chain, an optimization model is established and an improved tabu search algorithm is used to solve the problem. From the analysis, it shows that the total cost decreases as the total vehicles capacity increases, and the maximum utilization of alternative vehicles and the minimum cost of the system don’t occur at the same time in some cases.
Ventricular Assist Devices (VADs) are used to treat patients with cardiogenic shock. As the heart is unable to supply the organs with sufficient oxygenated blood and nutrients, a VAD maintains the circulation to keep the patient alive. The observation of the patient's hemodynamics is crucial for an individual treatment; therefore, sensors to measure quantifiable hemodynmaic parameters are desirable.
In addition to pressure measurement, the volume of the left ventricle and the progress of muscle recovery seem to be promising parameters. Ongoing research aims to estimate ventricular volume and changes in electrical properties of cardiac muscle tissue by applying bioimpedance measurement. In the case where ventricular insufficiency is treated by a catheter-based VAD, this very catheter could be used to conduct bioimpedance measurement inside the assisted heart. However, the simultaneous measurement of bioimpedance and VAD support has not yet been realized, although this would allow the determination of various loading conditions of the ventricle. For this purpose, it is necessary to develop models to validate and quantify bioimpedance measurement during VAD support.
In this study, we present an in silico and an in vitro conductivity model of a left ventricle to study the application of bioimpedance measurement in the context of VAD therapy. The in vitro model is developed from casting two anatomical silicone phantoms: One phantom of pure silicone, and one phantom enriched with carbon, to obtain a conductive behavior close to the properties of heart muscle tissue. Additionally, a measurement device to record the impedance inside the ventricle is presented. Equivalent to the in vitro model, the in silico model was designed. This finite element model offers changes in material properties for myocardium and the blood cavity.
The measurements in the in vitro models show a strong correlation with the results of the simulation of the in silico model. The measurements and the simulation demonstrate a decrease in impedance, when conductive muscle properties are applied and higher impedances correspond to smaller ventricle cross sections.
The in silico and in vitro models are used to further investigate the application of bioimpedance measurement inside the left heart ventricle during VAD support. We are confident that the models presented will allow for future evaluation of hemodynamic monitoring during VAD therapy at an early stage of research and development.
This paper uses the law of one price (LOP) and the DCC-GARCH method based on ten-day price sequences. The findings indicate that, compared with the international refined oil markets with mature market-oriented pricing mechanisms, only in the Chinese market do gasoline and diesel prices meet the LOP. This finding shows that, in the context of the gradual integration of the global refined oil market, the international level of China's refined oil price is still quite low. The price reforms pertaining to China's refined oil products still need to be pushed forward in the direction of marketization and internationalization.
With the continuous development of China's Internet economy, the model of grasping Internet economy benefit is diversified. Since 2016, the online celebrity economy has formed a trend of Internet marketing, and the online celebrity economic industry chain further has established along with the further development of MCN institutions. The relationship among the overall industry upstream and downstream sectors become closer and closer and even appear the trend of vertical cooperation. This paper is aimed at expressing the pricing mechanism of the online celebrity industrial chain and applies game theory and mathematical analysis to propose a reasonable pricing model
In the present manuscript, Crank Nicolson finite difference method is going to be applied to get the approximate solutions for the fractional Burgers equation. The fractional derivative used in this equation is going to be taken into consideration in the Caputo sense. The L1 type discretization formula is going to be applied to this equation. For checking the efficiency of proposed methods, the error norms L2 and L∞ have at the same time been calculated. Those newly got solutions using the presented method illustrate the easy usage and efficiency of the approach presented in this manuscript.
This paper described the volatility characteristic of the rate of return of financial asset by using QR-GARCH model, through introducing EVT model and constructing the extreme risk measure model based on QR-GARCH-EVT. In this paper, HS300 index data test was applied to show that under 5% significance level, and QR-GARCH-EVT model can effectively measure the risk value of the sample, but under 1% significance level. QR-GARCH-EVT model will underestimate the risk value of the sample to a certain degree, but generally speaking, compared with other models, the risk value measured by QR-GARCH-EVT model has a higher accuracy to enhance effectiveness.
This paper uses the interval quadratic preference loss function to establish the threshold model of exchange rate volatility by Taylor series expansion, and GMM method to study the intervention behavior of exchange rate. It found that the central bank has asymmetric intervention preference for exchange rate, discontinuous and nonlinear intervention for exchange rate, and there is an intervention threshold, and the central bank has a certain degree of “fear of appreciation” trend. To some extent, asymmetric interval intervention preference has resulted in the rapid growth of China's foreign exchange reserves.