Search Results - (( java segmentation using algorithm ) OR ( changes _ optimisation algorithm ))
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1
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Thesis -
2
Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm
Published 2019“…For optimisation purpose, this research proposed a relatively new algorithm called the Moth-Flame Optimisation (MFO). …”
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3
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Book -
4
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Proceeding Paper -
5
Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li
Published 2018“…From the simulation results, it was found that with the same number of PID controllers, the performance of AGC optimised by using MEPSO-TVAC algorithm is better in terms of overshoot and fitness value than using EPSO and PSO algorithms. …”
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6
Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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7
Multi-objective multi-verse optimiser for integrated two-sided assembly sequence planning and line balancing
Published 2022“…In this study, the 2S-ASPLB problem was formulated and optimised using Multi-Objective Multi-Verse Optimiser (MOMVO) by considering line efficiency, reorientation penalty, and tool change as the optimisation objectives. …”
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Article -
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Genetic algorithm for control and optimisation of exothermic batch process
Published 2013“…As such, another approach, GA is proposed to optimise the productivity without referring to a predetermined profile, namely genetic algorithm optimiser (GAO). …”
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9
Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation
Published 2016“…Hence, by implementing an optimisation method, the performance of the LFC can be optimised through optimising the PID controller parameters.…”
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10
Aco-based feature selection algorithm for classification
Published 2022“…An enhanced graph clustering ant colony optimisation (EGCACO) algorithm is proposed to solve the three (3) MGCACO algorithm problems. …”
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11
Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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Final Year Project / Dissertation / Thesis -
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Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm
Published 2019“…For the optimization, the robot will travel from one specific point to another with the predefined position within optimized gait and fastest time by using Ant Colony Optimization (ACO) technique. The algorithm being compared, between Ant Colony Algorithm (ACO) and the Particle Swarm Optimisation (PSO) in terms of time and distance. …”
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Optimisation and control of fed-batch yeast production using q-learning
Published 2013“…In a nutshell, QL is an alternative that can be considered to perform multiobjective optimisation in a frequently changing bioenvironment and suggest a substrate feeding profile that satisfied the process goal. …”
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14
A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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15
A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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16
Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim
Published 2019“…Thus, a reliable optimisation technique is crucial to address this issue. …”
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17
Application of the Bees Algorithm to find optimal drill path sequence
Published 2024“…When drilling multiple holes, 70% of the machining time is spent moving and changing tools. Therefore, optimising the drilling sequence is important to reduce the machining time and increase the production of the company. …”
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Proceeding Paper -
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Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub...
Published 2014“…AU simulation and optimisation works are carried out using gPROMS™. Two types of observations are made so as to study the performance of the proposed control algorithm mainly, the control of BGL values without meal disturbance and the control of BGL values following meals. …”
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Monograph -
20
Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II
Published 2016“…A full factorial experiment has been conducted to model surface roughness by controlling three variables; spindle speed, feed rate and depth of cut. Multi-objective optimisation has been performed using modified Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) with two levels crossover. …”
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