Search Results - (( global optimisation method algorithm ) OR ( rainfall optimization method algorithm ))
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1
Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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Thesis -
2
SINE COSINE ALGORITHM BASED NEURAL NETWORK FOR RAINFALL DATA IMPUTATION
Published 2024“…This chapter presents the ability of the sine cosine algorithm-based neural network (SCANN) to predict and optimize missing rainfall at different percentages of missing rates. …”
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Book Chapter -
3
Metaheuristic Algorithms and Neural Networks in Hydrology
Published 2024“…It starts with the introduction of ANNs as a black box model, followed by the coupling of various metaheuristic algorithms with ANNs to form novel neural network models for solving real-world problems in hydrology, including Particle Swarm Optimization (PSO) for rainfall-runoff modeling, Bat Optimization (Bat) and Cuckoo Search Optimization (CSO) for future rainfall prediction, the Whale Optimization Algorithm (WOA) and Salp Swarm Optimization (SSO) for future water level prediction, Grey Wolf Optimization (GWO), Multi-Verse Optimization (MVO), the Sine Cosine Algorithm (SCA) and the Hybrid Sine Cosine and Fitness Dependent Optimizer (SC-FDO) for imputing missing rainfall data.…”
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Book -
4
Rainfall prediction using multiple inclusive models and large climate indices
Published 2023Article -
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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Article -
6
Clustering of rainfall data using k-means algorithm
Published 2019“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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Conference or Workshop Item -
7
An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…This algorithm utilises first order optimisation method namely Gradient Descent (GD) method which attempts to minimise the error of network. …”
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Thesis -
8
Improvement Of Stereo Matching Algorithm Based On Sum Of Gradient Magnitude Differences And Semi-Global Method With Refinement Step
Published 2018“…A new stereo matching algorithm which uses improved matching cost computation and optimisation using the semi-global method (SGM) is proposed.The absolute difference is sensitive to low textured regions and high noise on the stereo images with radiometric distortions. …”
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Article -
9
Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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Thesis -
10
The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga
Published 2016“…Also, many of these PSO algorithms employed hybrid methods that integrate other optimisation algorithms with the standard PSO. …”
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11
Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation
Published 2019“…Exact algorithm is a sub-class of techniques that is able to guarantee global optimality. …”
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Weather Prediction for Strawberry Cultivation Using Double Exponential Smoothing and Golden Section Optimization Methods
Published 2024“…The system was developed by implementing the PHP programming language on the interface design as well as MySQL as a database processing. The algorithm used to predict the air temperature feature, wind speed feature, and rainfall feature was Double Exponential Smoothing, followed by the optimization of the Golden Section method to select the right smoothing value. …”
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Journal -
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An improved particle swarm optimization algorithm for data classification
Published 2023“…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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Article -
14
Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application
Published 2024“…This paper introduces the Gooseneck Barnacle Optimisation Algorithm (GBO) as a novel evolutionary method inspired by the natural mating behaviour of gooseneck barnacles, which involves sperm casting and self-fertilization. …”
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15
An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimisation
Published 2020“…One of the common efficient techniques to solve large-scale unconstrained optimisation issues is the conjugate gradient method, because of its simplicity, low memory consumptions and global convergence properties. …”
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Book Section -
16
Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor
Published 2019“…Heuristic optimisation method typically hinges on the efficiency in exploitation and global diverse exploration. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
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Proceeding Paper -
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…A coati optimization algorithm is introduced to select input scenarios. …”
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Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
Published 2013“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Sensitivity analysis of GA parameters for ECED problem
Published 2023“…Besides the conventional method by using the Lagrange Multiplier several evolutionary computation techniques such as Genetic Algorithm, Particle Swarm Optimisation, Ant Colony and Differential Evolution have been gaining popularity in solving general economic dispatch problems due to their desirable characteristics such as non-gradient dependent and ability to search for global optima. …”
Conference paper
