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A comparative sales forecast study between supervised and unsupervised learning algorithm on restaurant / Azhar Tamby
Published 2006“…In this research, there are two algorithm of neural network will be used. It is coming from supervised and unsupervised learning algorithm. …”
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Student Project -
2
Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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3
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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4
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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5
Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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Thesis -
6
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Multilevel learning in Kohonen SOM network for classification problems
Published 2006“…Classification is one of the most active research and application areas of neural networks. Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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8
Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood
Published 2015“…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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9
DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection
Published 2021“…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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Article -
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Self-organizing network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah
Published 2015“…The commonality between the aforementioned issues of concern is the adoption of Self—Organizing Network (SON) technology concept as the basis for the proposed solutions for the above-mentioned challenges. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia
Published 2015“…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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13
Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Article -
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate
Published 2025“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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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“…Next, the Real World Tournament Selection method is adapted and incorporated into the resource competition of Artificial Immune Recognition System. The proposed algorithms have been tested on a variety of datasets from the UCI machine learning repository. …”
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The effectiveness of problem-based serious games on learning and learning motivation in the context of 3D computer graphics / Meisam Moradi
Published 2022“…In addition, this study aimed at understanding the extent to which a problem-based SG can affect undergraduate students' learning motivation. Indeed, the literature shows that 3D computer graphic courses are replete with abstract notions and algorithmic concepts which make learning of it difficult. …”
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Automatic Grading System Of Incoming Raw Unclean Edible Bird Nest Using Deep Learning Model
Published 2021“…Therefore, a deep learning model with the self-learning ability on the feature extraction process and low human intervention was developed to solve the drawbacks of the human visual system and conventional algorithms. …”
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Monograph -
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Self-Organizing Network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah
Published 2016“…The commonality between the aforementioned issues of concern is the adoption of Self- Organizing Network (SON) technology concept as the basis for the proposed solutions for the above-mentioned challenges. …”
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