A Novel Instantaneous Frequency Algorithm and Its Application in Stock Index Movement Prediction

2012 ◽  
Vol 6 (4) ◽  
pp. 311-318 ◽  
Author(s):  
Liming Zhang ◽  
Na Liu ◽  
Pengyi Yu
2021 ◽  
pp. 1-19
Author(s):  
Sidharth Samal ◽  
Rajashree Dash

In recent years Extreme Learning Machine (ELM) has gained the interest of various researchers due to its superior generalization and approximation capability. The network architecture and type of activation functions are the two important factors that influence the performance of an ELM. Hence in this study, a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) oriented multi-criteria decision making (MCDM) framework is suggested for analyzing various ELM models developed with distinct activation functions with respect to sixteen evaluation criteria. Evaluating the performance of the ELM with respect to multiple criteria instead of single criterion can help in designing a more robust network. The proposed framework is used as a binary classification system for pursuing the problem of stock index price movement prediction. The model is empirically evaluated by using historical data of three stock indices such as BSE SENSEX, S&P 500 and NIFTY 50. The empirical study has disclosed promising results by evaluating ELM with different activation functions as well as multiple criteria.


2019 ◽  
Vol 85 ◽  
pp. 105784 ◽  
Author(s):  
Rajashree Dash ◽  
Sidharth Samal ◽  
Rasmita Dash ◽  
Rasmita Rautray

KURVATEK ◽  
2017 ◽  
Vol 1 (2) ◽  
pp. 21-31
Author(s):  
Fatimah Miharno

ABSTRACT*Zefara* Field formation Baturaja on South Sumatra Basin is a reservoir carbonate and prospective gas. Data used in this research were 3D seismik data, well logs, and geological information. According to geological report known that hidrocarbon traps in research area were limestone lithological layer as stratigraphical trap and faulted anticline as structural trap. The study restricted in effort to make a hydrocarbon accumulation and a potential carbonate reservoir area maps with seismic attribute. All of the data used in this study are 3D seismic data set, well-log data and check-shot data. The result of the analysis are compared to the result derived from log data calculation as a control analysis. Hydrocarbon prospect area generated from seismic attribute and are divided into three compartments. The seismic attribute analysis using RMS amplitude method and instantaneous frequency is very effective to determine hydrocarbon accumulation in *Zefara* field, because low amplitude from Baturaja reservoir. Low amplitude hints low AI, determined high porosity and high hydrocarbon contact (HC).  Keyword: Baturaja Formation, RMS amplitude seismic attribute, instantaneous frequency seismic attribute


CFA Digest ◽  
2003 ◽  
Vol 33 (3) ◽  
pp. 101-102
Author(s):  
Frank T. Magiera

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