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Article
Two-Stage Hybrid Feature Selection Approach Using Levy’s Flight Based Chicken Swarm Optimization for Stock Market Forecasting
Stock market forecasting is done by analyzing multivariate financial time series generated through technical analysis. However, high-dimensional data deteriorates the prediction performance due to irrelevant f...
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Chapter and Conference Paper
Exploring Label-Specific Feature Weights for Multi-label Feature Selection Using FWMABAC-MFS
Feature selection (FS) is a crucial task in multi-label learning as there are different numbers of labels and the dependencies between the labels and features need to be considered. This paper proposes a filte...
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Chapter and Conference Paper
A Multi-label Feature Selection Method Based on Multi-objectives Optimization by Ratio Analysis
Multi-label learning affected from curse of dimensionality, therefore, feature selection is vital. In this paper, we propose feature ranking method using one of the well-known Multi Attribute Decision Making (...
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Chapter and Conference Paper
Binary Chaotic Gray Wolf Optimizer-Based Feature Selection for Intrusion Detection: A Comprehensive Study and Performance Evaluation
The importance of Intrusion Detection Systems (IDS), also known as intrusion prevention systems, rests in the fact that they protect the security and integrity of computer networks. They accomplish this essent...
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Chapter and Conference Paper
Stock Market Forecasting Using Additive Ratio Assessment-Based Ensemble Learning
Stock market forecasting is fascinating yet challenging due to the influence of various factors. One such factor is sentiment which can influence the stock market movement. This paper considered historical sto...
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Article
A correlation-based feature weighting filter for multi-label Naive Bayes
Multi-label classification is used to solve the problem where multiple labels are associated with single sample. Naive Bayes (NB) classifier is widely used for single label classification due to its high perfo...
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Article
Portfolio management using Additive Ratio Assessment based stock selection and deep learning for prediction
Portfolio management plays a significant role in wealth management. A wise selection of assets in a portfolio may give a higher return. Higher returns are directly proportional to higher risk. The main concern...
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Article
A mutation-based modified binary fruit fly optimization for feature selection to predict CD4+/CD8+ T-cells epitopes
The healthcare sector is advancing with emerging technologies that help to detect new diseases or viruses worldwide. Generally, virus detection is based on various symptomatic tests and analysis of data sample...
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Article
Open AccessInferring linear-B cell epitopes using 2-step metaheuristic variant-feature selection using genetic algorithm
Linear-B cell epitopes (LBCE) play a vital role in vaccine design; thus, efficiently detecting them from protein sequences is of primary importance. These epitopes consist of amino acids arranged in continuous...
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Article
DL-TCNN: Deep Learning-based Temporal Convolutional Neural Network for prediction of conformational B-cell epitopes
Prediction of conformational B-cell epitopes (CBCE) is an essential phase for vaccine design, drug invention, and accurate disease diagnosis. Many laboratorial and computational approaches have been developed ...
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Article
gHPCSO: Gaussian Distribution Based Hybrid Particle Cat Swarm Optimization for Linear B-cell Epitope Prediction
Linear B-cell epitope (LBCE) identification is critical in develo** peptide-based vaccines, antibody production, and immuno-diagnosis. Laboratory experiments are costly and time-consuming for this endeavour....
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Article
Optimized fuzzy based symbiotic organism search algorithm for engineering design problem
Symbiotic Organism Search (SOS) is a novel metaheuristic algorithm based on reciprocal behaviour of organisms in environment by considering three imperative relationships such as mutualism, commensalism and pa...
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Article
Discrete Wavelet Transform-based feature engineering for stock market prediction
Stock market prediction is an interesting area of research where Technical Indicators (TI) play an important role. However, prediction of stock market movement is difficult due to the presence of noise and irr...
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Article
Binary Jaya algorithm based on binary similarity measure for feature selection
Feature selection (FS) has become an indispensable data preprocessing task because of the huge amount of high dimensional data being generated by current technologies. These high dimensional data contains irre...
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Chapter and Conference Paper
Ensemble Approach for Stock Market Forecasting Using ARIMA and LSTM Model
Stock market is a place where volatility is a major concern. At the same time, stock market data is not consistent due to missing information on some trading days. Forecasting of stock performance is challengi...
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Chapter and Conference Paper
Feature Selection Technique for Microarray Data Using Multi-objective Jaya Algorithm Based on Chaos Theory
Microarray datasets are high-dimensional data that contain the gene expression profiling information used for cancer classification. This causes a curse of dimensionality and poses multiple challenges in gene ...
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Chapter and Conference Paper
Global Best Guided Binary Crow Search Algorithm for Feature Selection
Feature selection is a universal combinatorial optimization problem that is used to enhance the characteristics of high-dimensional datasets by eliminating redundant data and selecting prominent features to ge...
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Chapter and Conference Paper
Stock Market Analysis of Beauty Industry During COVID-19
COVID-19 has significant influence on the financial market. This paper aimed to explore the COVID-19 scenario analysis for stock market of beauty industry. Stock data of Estée Lauder Companies (EL), Revlon Inc...
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Article
Effective forecasting of stock market price by using extreme learning machine optimized by PSO-based group oriented crow search algorithm
Stock index price forecasting is the influential indicator for investors and financial investigators by which decision making capability to achieve maximum benefit with minimum risk can be improved. So, a robu...
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Chapter
Global Best Guided Crow Search Algorithm for Optimization Problems
Crow search algorithm (CSA) is a nature-inspired metaheuristic algorithm that is emboldened by the social activity of intelligent bird. Crow preserves their surplus food from other crows which gives informatio...
