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Chapter and Conference Paper
Automated Fish Classification Using Unprocessed Fatty Acid Chromatographic Data: A Machine Learning Approach
Fish is approximately 40% edible fillet. The remaining 60% can be processed into low-value fertilizer or high-value pharmaceutical-grade omega-3 concentrates. High-value manufacturing options depend on the co...
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Chapter and Conference Paper
Operation-based Greedy Algorithm for Discounted Knapsack Problem
The discounted knapsack problem (DKP) is an NP-hard combinatorial optimization problem that has gained much attention recently. Due to its high complexity, the usual solution combines a global search algorithm...
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Chapter and Conference Paper
Multi-label Feature Selection Using Particle Swarm Optimization: Novel Initialization Mechanisms
In standard single-label classification, feature selection is an important but challenging task due to its large and complex search space. However, feature selection for multi-label classification is even more...
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Chapter and Conference Paper
A Novel Binary Particle Swarm Optimization Algorithm and Its Applications on Knapsack and Feature Selection Problems
Particle swarm optimisation (PSO) is a well-known evolutionary computation technique, which has been applied to solve many optimisation problems. There are two main types of PSO, which are continuous PSO (CPSO...
