Search Results - adaptive model difference ((selection algorithm) OR (optimisation algorithm))

An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

“…With various optimization algorithms available, choosing the one that best suits the deep learning model and dataset can make a substantial difference in achieving optimal results. …”
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Design of experiments meets immersive environment: optimising eating atmosphere using artificial neural network by Kantono, Kevin, How, Muhammad Syahmeer, Wang, Qian Janice

“…In this study, an artificial neural network (ANN) with particle swarm optimisation algorithm (PSO; hereafter ANN-PSO) was selected and compared with classical Response Surface Method (RSM) as ANN-PSO has been reported to yield better reliability and predictability compared to RSM. …”
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Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS by Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abd Ghani, Tokhi, M. O.

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Energy efficient cluster head distribution in wireless sensor networks by Siew, Zhan Wei

“…Evaluation and assessments have been carried out through simulation under different network topologies and it shows that FLCH selection improved first node dies (FND) round by 26.88 % as compared to LEACH. …”
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A comparative study for parameter selection in online auctions by Gan, Kim Soon

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Multivariable adaptive lyapunov fuzzy controller for pH neutralisation process by Zanil, M.F., Hussain, Mohd Azlan

“…The optimised structure is used to predict three-difference control action simultaneously. …”
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Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling by Al-Betar, Mohammed Azmi

“…The major thrust of this algorithm lies in its ability to integrate the key components of populationbased methods and local search-based methods in the same optimisation model. …”
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

“…The proposed controller is a hybrid model reference adaptive speed controller (HMRASC) which mainly consists of two functional blocks. …”
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Multivariable Adaptive Lyapunov Fuzzy Controller for pH Neutralisation Process by Zanil, M.F., Hussain, Mohd Azlan

“…The optimised structure is used to predict three-difference control action simultaneously. …”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

“…The first part involves a review of prior locustinspired algorithms, while the second part concerns the adaptation of the algorithm to the cloud computing paradigm. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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Optimisation and performance evaluation of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the prediction o... by Chong, D.J.S., Chan, Y.J., Arumugasamy, S.K., Yazdi, S.K., Lim, J.W.

“…Confirmatory experiments were carried out in the biogas plant under this set of optimised variables for a period of two months. The predicted biogas production and methane yield are highly correlated to the actual data with small percentage difference of 1.25 and 5.09 respectively, indicating that ANFIS model was accurate and reliable. …”
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Investigation And Development Of Forensic Mean-Based Adaptive Background Correction Algorithm (Mabca) For Visual Enhancement Of Bloodstains, Seminal Stains And Fingerprints by Lee, Wee Chuen

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EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

“…Throughout this research study, models like Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Adaptive Boosting (AdaBoost) will be explored. …”
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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

“…Post-optimization ANN model was trained using eleven different leaning algorithms. …”

Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Adapting And Hybrid Ising Harmony Search With Metaheuristic Components For University Course Timetabling by Al-Betar, Mohammed Azmi

“…The major thrust of this algorithm I ies in its abiiity to integrate the key components of populationbased methods and local search-based methods in the same optimisation model. …”
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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

“…However, predicting software defects with irrelevant features and overlapping classes is challenging and can lead to lengthy training and low model accuracy. To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.