Search Results - (( using auto problem algorithm ) OR ( evolution optimisation system algorithm ))
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Optimisation of Biochemical Systems Production using Hybrid of Newton Method, Differential Evolution Algorithm and Cooperative Coevolution Algorithm
Published 2017“…The proposed method is used to solve the optimisation problem in optimise the production of biochemical systems. …”
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Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage
Published 2023“…Electric power factor; Electric power transmission networks; Evolutionary algorithms; Optimization; Differential Evolution; Differential evolution algorithms; Distributed generation source; Multiple distributed generations; Optimal allocation; Optimisations; Power factorAbstract; Power system constraints; Distributed power generation; algorithm; distribution system; energy planning; operations technology; optimization…”
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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. …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…A case study taken from database, provided by Le2i Universite de Bourgoune is used to evaluate the performance of the Bat Algorithm. …”
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A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem
Published 2022“…This paper studies the correlation of different parameters selection in Bat Algorithm in solving the camera auto-calibration problem. …”
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A Comparative Study of the Application of Swarm Intelligence in Kruppa-Based Camera Auto-Calibration
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Conference or Workshop Item -
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Auto-encoder variants for solving handwritten digits classification problem
Published 2020“…Auto-encoders (AEs) have been proposed for solving many problems in the domain of machine learning and deep learning since the last few decades. …”
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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). …”
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Thesis -
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Comparisons of automated machine learning (AutoML) in predicting whistleblowing of academic dishonesty with demographic and theory of planned behavior
Published 2023“…The findings of this study will be a great interest of many research scholars to conduct a more in-depth analysis on AutoML for many domains mainly in education and academic misconduct fields. â�¢ AutoML is the first of its kind to be empirically compared between TPOT and AutoModel in an application to predict academic dishonesty whistleblowing. â�¢ Besides accuracy performances of the AutoML, the proportion of the variance of each attribute from demographic and Theory of Planned Behavior (TPB) is also presented in the prediction models of academic dishonesty whistleblowing. â�¢ AutoML is a convenient and reproducible rapid modeling method of machine learning to be used in many kinds of prediction problem. …”
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Auto-formation group chat for fitness application with rule-based / Amar Aslam Ramli
Published 2018“…Moreover, the algorithm used for rule-based expert system is forward chaining method. …”
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Student Project -
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A Mobile Application For Stock Price Prediction
Published 2021“…A mobile application for stock price prediction using time series algorithms is developed to tackle the problem mentioned. …”
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Final Year Project / Dissertation / Thesis -
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…Therefore, in this research, a new model namely Encoder Simplified GRU (ES-GRU) is proposed to reduce dimension of data using an Auto-Encoder (AE). Accordingly, the reset gate is replaced with an update gate in order to reduce the redundancy and complexity in the standard GRU. …”
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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. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution
Published 2014“…The current approach in the literature has been largely based on trial and error, while most of the reported optimization approaches have limited the domain of the problem to a single objective problem. This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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Fault detection of aircraft engine components using fuzzy unordered rule induction algorithm
Published 2016“…State-of-the-art systems are not accurate due to high dimensionality of sensory data. This paper proposes auto encoder neural network for compressing of high dimensional sensory data and classification using Fuzzy Unordered Rule Induction Algorithm (FURIA) with emphasis on detection and isolation of incipient faults. …”
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Proceeding Paper -
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Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data
Published 2025“…The extracted features were the input for AutoML, an automatic algorithm selection that was measured by Bayesian Optimization algorithm to select the best performance model. …”
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