Search Results - (( intelligence based data algorithm ) OR ( intelligence series based algorithm ))*
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Time series data intelligent clustering algorithm for landslide displacement prediction
Published 2018“…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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Development of an intelligent prediction tool for rice yield based on machine learning techniques
Published 2006“…Whereas kernel-based clustering algorithm is developed for finding clusters in climate data. …”
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Development of hybrid artificial intelligent based handover decision algorithm
Published 2017“…The performance of the newly developed k � step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. …”
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WiMAX Traffic Forecasting Based On Artificial Intelligence Techniques
Published 2024thesis::doctoral thesis -
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Hybrid intelligent approach for network intrusion detection
Published 2015“…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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An algorithm for the selection of planting lining technique towards optimizing land area: an algorithm for planting lining technique selection
Published 2012“…This algorithm solution generated the dataset based coordinates areas to analyze the techniques. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…A series of empirical studies with different benchmark data sets is conducted. …”
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Hybrid Genetic Algorithm based Fuzzy Inference System for Data Regression
Published 2023Conference Paper -
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Enhancing electricity consumption forecasting in limited dataset: A simple stacked ensemble approach incorporating simple linear and support vector regression for Malaysia
Published 2025“…Analysis revealed that this simple stacked ensemble SVR-based time-series algorithm, employing an ε -insensitive loss function with a third-degree polynomial kernel, outperformed 71 other SVR-based algorithms, including four time-series algorithms from the previous study. …”
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Classification of JPEG files by using extreme learning machine
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Comparative performance of machine learning algorithms for cryptocurrency forecasting
Published 2018“…Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. …”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024thesis::master thesis -
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A comparative study and simulation of object tracking algorithms
Published 2020“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.]
Published 2017“…Researchers then performed data preprocessing on the data. Afterwards, data mining algorithms were applied in order to forecast electric load. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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