Search Results - (( location selection learning algorithm ) OR ( whale optimisation based algorithm ))
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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
Published 2021“…In this paper, we propose a metaheuristic method for feature extraction algorithm with Whale Optimisation Algorithm (WOA) based HCR. …”
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Impact of Balanced Exploration and Exploitation on High-dimensional Feature Selection with Hierarchical Whale Optimisation Algorithm
Published 2024“…While metaheuristic algorithms like the Whale Optimisation Algorithm (WOA) have shown promise in addressing these challenges, stability issues are least addressed. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Having those said, this study proposes BESS optimisation to reduce the total system losses using modified Whale Optimisation Algorithm (WOA) with high exploration and exploitation features. …”
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Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms
Published 2021“…Least Square Support Vector Machine (LSSVM) base models with linear kernel, polynomial kernel and Radial Basis Function (RBF) kernel and its hybrid models with integration of Hybrid of Particle Swarm Optimisation and Genetic Algorithm (HPSOGA), Whale Optimisation Algorithm based on Self-adapting Parameter Adjustment and Mix Mutation Strategy (SMWOA) and Ameliorative Moth Flame Optimisation (AMFO) were developed and used to predict the WQI at stations 1K06, 1K07 and 1K08 of the Klang River in Selangor, Malaysia. …”
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Optimization of multi-holes drilling path using particle swarm optimization
Published 2022“…The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). …”
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Investigating dam reservoir operation optimization using metaheuristic algorithms
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…By preserving the equilibrium between the proposed MHAs and reservoir risk analysis indices, the stakeholder can select or control the optimal KGD operation by referring to the summary of findings for the observed period assessments. The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Final Year Project / Dissertation / Thesis -
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion
Published 2025“…For all five locations, four ML algorithms have been trained, tested, and then evaluated: long short-term memory (LSTM), extreme gradient boost (XGBoost), Artificial Neural Network (ANN), and Support Vector Regression (SVR). …”
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Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan
Published 2020“…Therefore, this project is focused on predicting the location of soil erosion by using logistic regression Machine Learning algorithm and GIS. …”
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Final Year Project -
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Assessment of suitable hospital location using GIS and machine learning
Published 2022“…First, the conditioning factors were optimized and ranked to identify and select the most correlated factors to predict the suitability of a hospital site by applying the correlation feature selection (CFS) algorithm and the greedy-stepwise search method. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Convolution Neural Network (CNN) using deep learning algorithm is chosen in identifying frequency of movement and execution time of housebreaking crime. …”
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Efficient multi-agent deep reinforcement learning algorithm for multi UAV collision avoidance
Published 2026“…We propose both curriculum learning and transfer learning by adding more agents over time and subsequently employing learning models. …”
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Optimizing the travel distance between mosque and muslim affair activities using Delaunay Triangulation / Siti Nor Dalila Shamsul Bahar
Published 2019“…In this study, incremental algorithms of Delaunay triangulation are form based on the location of the mosques in Perlis. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…Furthermore, the efficacy of different models based on heuristic hyperparameter tuning is evaluated in which the different kernel function for Support Vector Machine, various distance metrics of k-Nearest Neighbors. The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Development Of Construction Noise Prediction Method Using Deep Learning Model
Published 2021“…Seven deep learning models trained by seven noise datasets with different aspect ratios were selected and implemented in the proposed noise prediction model. …”
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Final Year Project / Dissertation / Thesis
