Search Results - (( variable learning path algorithm ) OR ( evolution optimisation based algorithm ))
Search alternatives:
- evolution optimisation »
- optimisation based »
- path algorithm »
- learning path »
- variable »
-
1
-
2
Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
Get full text
Get full text
Get full text
Article -
3
A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
Get full text
Get full text
Get full text
Article -
4
A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
Get full text
Get full text
Get full text
Article -
5
A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
Get full text
Get full text
Get full text
Article -
6
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. …”
Get full text
Get full text
Book Section -
7
IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE
Published 2017“…Behaviour-based architecture is one of the most effective autonomous navigation techniques, second only to machine learning. However, specific algorithm may only be effective for a specific environment. …”
Get full text
Get full text
Final Year Project -
8
Destination prediction based on past movement history
Published 2020“…The results are promising and we also look at the combination of variables to use for such a use case.…”
Get full text
Thesis -
9
B-spline curve fitting with different parameterization methods
Published 2020“…After generating control points, distance between the generated and original data points is used to identify the error of the algorithm. Later, genetic algorithm and differential evolution optimization are used to optimise the error of the curve. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
10
Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
Get full text
Get full text
Get full text
Thesis -
11
Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
12
Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation
Published 2017“…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. An adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order for the mobile robot to learn. …”
Get full text
Get full text
Get full text
Thesis -
13
-
14
iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…In addition, a new optimisation model for finding optimum parameter values in the MEDF and an algorithm for transmuting a 1D quantitative feature into a respective categorical feature are developed to facilitate the model. …”
Get full text
Get full text
Get full text
Article -
15
Dynamics and control of underactuated systems with applications in robotics / Ahmad Azlan Mat Isa … [et al.]
Published 2011“…If all underactuated systems in a class can be transformed into a specific class of nonlinear systems, we refer to Artificial Neural Network (ANN) systems as the "normal form" of the corresponding class of underactuated systems. An adaptive learning algorithm using an artificial neural network ANN has been utilized to predict the passive joint position of underactuated robot manipulator. …”
Get full text
Get full text
Research Reports -
16
A self‐configured link adaptation for green LTE downlink transmission
Published 2015“…Current and next‐generation cellular networks require such interactive techniques in order to be self‐optimised without complex modifications.…”
Get full text
Get full text
Article -
17
Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia
Published 2019“…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
Get full text
Get full text
Thesis -
18
Development of tool life prediction model of TiAlN coated tools during the high speed hard milling of AISI H13 steel
Published 2011“…Shunmugam et al. [7] also combined RSM with differential evolution and genetic algorithms to draw a comparison between these methods. …”
Get full text
Get full text
Get full text
Book Chapter
