Search Results - data distribution ((((window algorithm) OR (learning algorithm))) OR (bat algorithm))
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An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms
Published 2021“…Therefore, to overcome these problems, this study proposed an improved dynamic load balancing technique known as HBAC algorithm which dynamically allocates task by hybridizing Artificial Bee Colony (ABC) algorithm with Bat algorithm. …”
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Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms
Published 2019“…Hence, the mapping of oil palm distributions via machine learning algorithm was better than that via non-machine learning algorithm.…”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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Web based applications for energy management system incorporated network reconfiguration using genetic algorithm / Wan Adnan Wan
Published 2006“…The development on Web Application system uses An ActiveX technology approach. The Genetic Algorithm Based Network Reconfiguration Technique for loss minimization in the UiTM Distribution System is also proposed based on general combinatorial optimization algorithm. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. Three LIRP models involving multiple distribution centers and periods are proposed. …”
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Classification of diabetic patients with imbalanced class distribution by using a Cost-Sensitive forest algorithm / Ummi Asyiqin Che Muhammad and Muhammad Hasbullah Mohd Razali
Published 2023“…Although many machine learning algorithms have been developed by researchers, the class imbalanced distribution still makes it challenging for classifiers to properly learn and differentiate between the minority and majority classes. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…However, the problem of learning or inferencing the posterior distribution of the algorithm is trivial. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…However, the problem of learning or inferencing the posterior distribution of the algorithm is trivial. …”
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Performance evaluation and enhancement of EDCA protocol to improve the voice capacity in wireless network
Published 2017“…The idea of the algorithm was based on creating different contention window ranges between access point and wireless workstations, and changing the technique of increasing the contention window value when the collision happened. …”
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Simulation of Empty Container Logistic Management at Depot
Published 2017“…Then, the feasible route with the minimum cost will be determined by applying the proposed heuristic algorithm. The heuristic algorithm can be divided into three main phases which are data sorting, data assigning and time window updating.…”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…Moreover, generated topological networks cannot represent the distribution of data. In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System
Published 2019“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System
Published 2019“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition
Published 2010“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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