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1
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Article -
2
Improving the evaluation performance of space-time trellis code through visualisation
Published 2011“…To our knowledge, although visualisation is widely used to handle a variety of problems, it has never been employed specifically to solve complexity problems that are related to generator matrix G evaluation. …”
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Conference or Workshop Item -
3
Improving the evaluation performance of space-time trellis code through STTC visualisation tool
Published 2013“…To our knowledge, although visualisation is widely used to handle a variety of problems, it has never been employed specifically to solve complexity problems that are related to generator matrix G evaluation. …”
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Article -
4
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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5
Classification with degree of importance of attributes for stock market data mining
Published 2004“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Article -
6
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Article -
7
Agro-ento bioinformation: towards the edge of reality
Published 2002“…The primers, which entrain processes, both natural and man-induced, include mechanisms such as protocols, algorithms, visualisations, and structural and visual designs. …”
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Inaugural Lecture -
8
Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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10
Automated Detection and Classification of Retinal Vein Occlusion Using Ultra-widefield Retinal Fundus Images and Transfer Learning
Published 2024“…The approach seeks to utilise knowledge from pretraining to enhance the performance of the segmentation model. …”
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Thesis -
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Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Subsequently, comparative analysis to further establish the problems has been carried out via utilization of various existing algorithms which were then validated using three openly available datasets. …”
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Thesis