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A Hybrid Stock Selection Model Based on Forecasting, Classification and Feature Selection
Shiliang Zhang,Tingcheng Chang 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.6
The basic aim of this paper is to provide a model to explain stock performance paramount level. To reach this purpose, this research proposes that rough set theory (RS), allied with the use of Grey Prediction, Semi-Supervised Graph Regularized Non-negative Matrix Factorization (SGNMF), K-means and Grey Relation, can out-perform the more standard approaches that are employed in economics. This study focuses on stock to select the optimal stock portfolio out applying the financial statement datum from the New Taiwan Economy database (TEJ). Firstly, this study collects relative financial ratio datum as the conditional attributes selection and then uses GM(1,1) for forecasting, SGNMF for choosing the more important conditional attributes, and rough set for figuring the best portfolio out. Finally, the Grey relational analysis is used to reduce the investment risk for fund allocation. This study will demonstrate that rough sets model is applicable to stock portfolio. The empirical result in Taiwan: During five years (2009-2013), the average annual rate of return was 20.41%, the accumulated rate of return for 9 quarter was 61.22%. The portfolio determined by the model is a promising alternative to the conventional methods for economic and financial prediction..
Lightweight Design of an Electric Tricycle Frame Considering Dynamic Stress in Driving Conditions
Pan Longye,Zhu Xiangqian,Li Yang,Guan Tingcheng 한국자동차공학회 2021 International journal of automotive technology Vol.22 No.4
Since most tricycles are driven on rough roads, a static analysis of the frame with a constant load and a specific boundary condition is insufficient to assess whether the lightweight design satisfies the strength requirements. A flexible multibody dynamics approach is used to assess the dynamic stress of a tricycle frame in five driving conditions to determine the positions where material can be removed. The five driving conditions, including high-speed driving, turning, climbing, braking and driving on a bumpy road, are established according to two national standards. An electric tricycle prototype is modeled using the rigid-flexible coupling method, and experiments are conducted to adjust the center of mass and stiffness of the suspension. The frame stress results obtained from the simulation are in good agreement with the loading test results. Subsequently, the dynamic stress of the frame is analyzed, and a steel plate with a suitable thickness is selected according to the stress distribution and the allowable stress. The modified frame is about 19.1 % lighter, and the maximum stress is only 2.8 % larger than that of the prototype. The results demonstrate that the proposed method is suitable for the lightweight design of one component in a system operating under various working conditions.