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Volume 07 Issue 03 (March 2020)

S.No. Title & Authors Page No View

Title : Apply Support Vector Regression to Forecast Stock Prices with Feature Selection through Clustering

Authors : Chih-Ming Hsu

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Abstract :

Accurately forecasting future stock prices is an essential and important issue for an investor to make an expected profit, as well as decrease the investment risk. In the past, the topic that determines the factors crucial to the forecasting of future stock prices is rarely addressed. In this study, the support vector regression and TwoStep cluster analysis are integrated to propose an approach for tackling the stock price forecasting problems with a function of feature selection. The feasibility and effectiveness of the proposed method are validated through making a case study on three different levels’ indices that include the TAIEX, FTSE TWSE Taiwan 50 Index, and Taiwan 2303 Stock. The experimental results show that the feature selection mechanism can efficiently screen out the critical technical indicators for forecasting the future stock prices, as well as can remove the superfluous indicators that might interfere the forecasting abilities of other critical technical indicators. Next, the feature selection procedure can greatly reduce the total number of technical indicators to prevent the over-fitting of training the training data. The selected best simplified forecasting model cannot always provide better forecasting performance. However, the investors can only pay attention to less technical indicators, and can obtain a satisfactory forecasting result with a high accuracy. Hence, an investor can save time, cost, and effort while building a forecasting model, thus make more concentration on fewer financial analysis and trading strategies.


Title : The Effect of the Outlet Geometry on the Velocity Profiles of Hydro cyclones

Authors : Tathagatha Mukherjee, Tirthankar Mukherjee

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Abstract :

The present study aims at investigating the effects of different shapes of the overflow tube on the pressure drop in the hydrocyclone. The pressure drop is a measure of the energy required to operate a hydrocyclone unit, and due to its continuous operation, the lowest possible value is preferred. Three different models are analyzed viz. the tapered overflow tubes and a standard model. The former consists of two variants: the first with inclination of 2° inwards (referred to as HC1) and the second with inclination of 2° outwards (referred to as HC3), whereas the latter variant is a straight tube with no inclination (referred to as HC2). Block structured mesh has been generated using ICEM CFD with cell faces aligned along curved streamlines to reduce numerical diffusion.

Large-eddy simulation (LES) is used to directly resolve large eddies, whereas the smaller eddies are modeled with standard Smagorinsky model. The simulation has been carried on in Hsieh and Rajamani hydrocyclone model using LES which has no deviation in the vortex finder. Flow is developed in steady state and dust particles were injected after the air-core formation in transient state. Same working conditions were applied on the altered hydrocyclone models. The codes of ANSYS Fluent has been used for numerical study.

Conclusive results indicate that the pressure drop is highly sensitive to the shape of the overflow pipe in hydrocyclones. This study points out the main factors of improving performance of hydrocyclones which simplifies the decision making of engineers.


Title : Leagility, New Paradigm Logistic Performance Measurement System

Authors : S.A. Kamel Kaya, N. Messaoudi

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Abstract :

The link between the lean orientation and the agile model is only possible through the Supply Chain interface (SC) and the DC (Demand Chain), called "leagility." What does this concept cover? How is it achieved? The answer to this second question suggests a multidimensional repository based on the triptych: efficiency, efficacy, and responsiveness, the combination of which allows us to define not only the three determinants but also the related Key Performance Indicators (KPIs). It requires the use of instruments such as the Advanced Available To Promise Mode Batch (AATP MB / Time Real) to achieve a compromise between the objectives of the SC and those of the DC.