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i-Saturate: The New Discovery of Stopping Criterion in Genetic Algorithm
Published 2020“…It was found that the performance of the developed model was good at the low mutation rate (0.01,0.02) but the i-Saturate model was better when mutation rate was greater than 0.03. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill
Published 2019“…This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. …”
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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Experimenting the dendrite cell algorithm for disease outbreak detection model
Published 2014“…The characteristics of early outbreak signal which are weak and behaved under uncertainties has brought to the development of outbreak detection model based on dendrite cell algorithm.Although the algorithm is proven can improve detection performance, it relies on several parameters which need to be defined before mining.In this study, the most appropriate parameter setting for outbreak detection using dendrite cell algorithm is examined.The experiment includes four parameters; the number of cell cycle update, the number of dendrite cell allowed to be in population, weight, and migration threshold value. …”
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Mobile game application development using evolutionary algorithms
Published 2014“…Hence it has opened up a whole new market with its mass among users and attracted a large number of smartphone application developers. Evolutionary Algorithms have never been used on mobile applications, thus it gives a novel idea of utilizing Evolutionary Algorithms in developing applications typically in games for mobile platforms. …”
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Prediction of football club winning rate using Bayesian model algorithm / Adam Khairul Anuar
Published 2023“…Despite technological progress, a gap exists in fully incorporating big data into football analytics, which this research aims to address through Bayesian models. Objectives involve studying, developing, and evaluating the accuracy of a Bayesian model for predicting winning rates. …”
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Ensemble dual recursive learning algorithms for identifying flow with leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
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Machine learning algorithms in context of intrusion detection
Published 2016“…Many machine learning techniques have been developed to cope with this problem. These machine learning algorithms develop a detection model in a training phase. …”
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Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm
Published 2019“…However, large amount of samples need to be generated for the training process of the ANN for the modeling of a complex design, resulting in a high neural model development cost. …”
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A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis
Published 2024thesis::doctoral thesis -
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Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication
Published 2021“…Thus, the LDPC code encoder model is developed to identify a low complexity encoding algorithm of LDPC code for the DF protocol relay system. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Integration of global search algorithm into ANN model further improved the model performance. …”
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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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Target heart rate zone detector during exercise based on real-time facial expression using single shot detection algorithm / Muhammad Azziq Shamsudin, Raihah Aminuddin and Ummu Mar...
Published 2022“…Their facial expression is measure and determine based on Rating of Perceived Exertion (RPE) scale. The object detection machine learning model used in this project is Single Shot Detector (SSD) algorithm. …”
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