Search Results - (( intelligence based growth algorithm ) OR ( intelligence based data algorithm ))*
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. Naïve Bayes is an intelligent method that depends on Bayes’ probability theory integrated with Adaptive Weight Ranking Policy (AWRP) via dynamic aging factor to improve the response time and network performance. …”
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
Published 2024“…Electric power production data has the characteristics of massive data scale, high update frequency and fast growth rate. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…Many fields such as data science, data mining suffered from the rapid growth of data volume and high data dimensionality. …”
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An intelligent DDoS attack detection tree-based model using Gini index feature selection method
Published 2023“…This paper proposes a novel intelligent DDoS attack detection model based on a Decision Tee (DT) algorithm and an enhanced Gini index feature selection method. …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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Citation Index Journal -
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An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification
Published 2022“…In this connection, a recent dataset, â��Mocap Hand Postures Data Set,â�� has been opted to employ the different variants of the machine learning algorithm. …”
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Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin
Published 2020“…Thus, this project proposes a solution to the problems by utilizing the machine learning approach which is the Agglomerative clustering algorithm. Previous studies shows that homogenous grouping of autistics students yields positive results, therefore, this project proposes to design and develop a clustering model system known as the CASDSS (Clustering Autism Spectrum Disorder Students System) where the main goal of this system is to create a homogenous grouping of the ASD students based on their behaviour, skills and intelligence. …”
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iBUST: An intelligent behavioural trust model for securing industrial cyber-physical systems
Published 2024“…For this intelligent TMM, a variant of Frequency Pattern Growth (FP-Growth), called enhanced FP-Growth (EFP-Growth) algorithm is developed by altering the internal data structures for faster execution and by developing a modified exponential decay function (MEDF) to automatically calculate minimum supports for adapting trust evolution characteristics. …”
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Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions
Published 2018“…The explosive growth of data in volume, velocity and diversity that are produced by medical applications has contributed to abundance of big data. …”
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Automated scheduling of hostel room allocation using genetic algorithm
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Conference or Workshop Item -
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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…There has been a rapid growth in using Artificial Immune Systems for applications in data mining and computational intelligence recently. …”
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Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming
Published 2024“…To address these challenges, an innovative Artificial Intelligence-based (AI-based) predictive algorithm has been proposed, leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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A machine learning approach to movie recommendation system
Published 2025“…This project presents a machine learning-based movie recommendation system aimed at providing accurate and personalized movie suggestions while addressing common industry challenges such as biased recommendations, data sparsity, and the cold start problem. …”
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Final Year Project / Dissertation / Thesis -
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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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Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph
Published 2023“…The conference theme, 'Re-thinking the dynamization between environmental issues and adaptive technology for inclusive growth,' saw Prof. Corina delivering her speech titled "AI and SDGs: Resource-Based View Perspective." …”
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Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes
Published 2025“…The research leverages Artificial Intelligence (AI)-based Genetic Algorithms (GA) and game theory to address critical challenges in resource allocation. …”
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A novel approach to data mining using simplified swarm optimization
Published 2011“…This deficiency has prompted the need for a new intelligent data mining technique based on stochastic population-based optimization that could discover useful information from data. …”
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Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks
Published 2021“…The quality of data collected from sensors greatly influences the performance of the modelling processes using ML algorithms. …”
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