Search Results - (( data distribution a algorithm ) OR ( parameter adaptation _ algorithm ))*
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1
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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2
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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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…This paper present an analysis of inbound internet traffic and development of Adaptive Policing and Shaping Algorithms on inbound internet traffic and fitted to traffic model. …”
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4
Slice sampler and metropolis hastings approaches for bayesian analysis of extreme data
Published 2016“…The slice sampler method can adaptively change the scale of changes made, which makes it easier to tune than Metropolis Hastings algorithm. …”
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5
Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy
Published 2023“…Air quality; Decision making; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Inference engines; Mapping; Mean square error; Multiobjective optimization; Optimal systems; Particle swarm optimization (PSO); Quality control; Renewable energy resources; Solar radiation; Uncertainty analysis; Adaptive neuro-fuzzy inference system; ANFIS; Multi objective algorithm; Multi objective particle swarm optimization; Multi-objective genetic algorithm; Renewable energies; Renewable energy generation; Solar radiation forecasting; Parameter estimation…”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data generated from network traffic are called concept drift. …”
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7
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. Two parameters (population size and generation numbers) are adaptively adopted from number of remaining ranking features. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. …”
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10
Transferring near infrared spectroscopic calibration model across different harvested seasons using joint distribution adaptation
Published 2022“…Thus, this study aims to investigate the ability of Joint Distribution Adaptation (JDA) transfer learning algorithm in addressing the assumption of traditional machine learning i.e. both training and testing data must come from the same feature spaces and data distribution. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Performance evaluation and enhancement of EDCA protocol to improve the voice capacity in wireless network
Published 2017“…Through the proposed algorithm, the Minimum Contention Window (CWmin) and Arbitration Inter Frame Space (AIFS) parameters were adapted based on the percentage of the collision in the network. …”
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13
Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks
Published 2017“…In the first part of the thesis, distributed power control and beamforming algorithm is proposed in which users operating in the underlay mode can strategically adapt their power levels and maximize their own utilities. …”
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14
Variational Bayesian inference for exponentiated Weibull right censored survival data
Published 2023“…It also has the strength of adapting unimodal functions with bathtub shape. Estimating the parameter of EWD distribution poses another problem as the flexibility calls for the introduction of an additional parameter. …”
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15
Multi agent quality of service routing based on scheme ant colony optimization algorithm
Published 2014“…In saturated load, efficiency is a very important parameter and a few changes in it can result in high performance of network to delivery of data.…”
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16
Optimizing LSTM S2S models with Evolutionary Mating Algorithm (EMA) for direct multi-step forecasting of household electrical power consumption
Published 2026“…This study proposes a hybrid approach that combines a Long Short-Term Memory Sequence to Sequence (LSTM S2S) model with the Evolutionary Mating Algorithm (EMA) to optimize the model settings. …”
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Water quality monitoring using machine learning and IoT: a review
Published 2024“…However, with the emergence of machine learning (ML) and Internet of Things (IoT) technologies, the process of water quality monitoring and analysis has become more efficient, accurate, and cost-effective. ML algorithms can analyze large volumes of water quality data, enabling data-centric approaches to designing, supervising, simulating, assessing, and refining various water treatment and management systems. …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit
Published 2024“…Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. …”
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19
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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20
Instance matching framework for heterogeneous semantic web content over linked data environment
Published 2021“…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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