Search Results - (( using mobile learning algorithm ) OR ( using optimization method algorithm ))
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Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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Proceedings -
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Thesis -
3
Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…This research proposed automated feature selection using Boruta algorithm to detect the malware. The proposed method adopts machine learning prediction and optimizes the selecting features in order to reduce the model of machine learning complexity. …”
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Article -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Multi-Robot Learning with Bat Algorithm With Mutation (Bam)
Published 2022“…Multiple techniques like swarm optimization, cuckoo algorithm and other such algorithms are under study for multi robotic systems. …”
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Undergraduates Project Papers -
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Final Year Project / Dissertation / Thesis -
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Artificial intelligent power prediction for efficient resource management of WCDMA mobile network
Published 2023“…The output of SVR will be used by WCDMA mobile network to decide on new service admission. …”
Conference Paper -
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Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm
Published 2024“…Secondly, this work designs optimization measures from inertia weight and learning factor to build an improved particle swarm optimization algorithm (IPSO). …”
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Deep reinforcement learning online offloading for SWIPT multiple access edge computing network
Published 2021“…Deep Q network (DQN) is used to learn the binary offloading decisions from the learning experience. …”
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Proceedings -
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Mobile application: coin identification using machine learning / Dania Qistina Mohd Nazly
Published 2021“…Most of the human work has been replaced by computers in recent years. With the rise of mobile technology and Internet access, recent developments in machine learning have designed many algorithms to solve diverse human problems. …”
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Thesis -
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Behavioural Feature Extraction For Context-Aware Traffic Classification Of Mobile Applications
Published 2018“…This thesis identified domain-specific features that are effective for accurate, large-scale and scalable mobile applications classification using machine learning techniques. …”
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A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone
Published 2019“…Subjective evaluation by selected respondents are also has been made using Absolute Category Rating method as recommended by ITU to evaluate EnVADE algorithm in term of QoE. …”
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A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone
Published 2019“…Subjective evaluation by selected respondents are also has been made using Absolute Category Rating method as recommended by ITU to evaluate EnVADE algorithm in term of QoE. …”
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15
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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Comparative Analysis of Pneumonia Detection from Chest X-Ray Images Using CNN And Transfer Learning
Published 2024“…On a dataset of accessible pneumonia X-rays, the method was tested. This research shows which neural network algorithm is optimal for detecting pneumonia, and how medical practitioners might use it in the actual world. …”
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Article -
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Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…Firstly, the customer’s dataset was generated using Faker Python package. Secondly was the pre-processing which includes the dimensionality reduction of the dataset using the PCA technique and finding the optimal number of clusters using the Elbow method. …”
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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad
Published 2016“…The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
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Discovering optimal features using static analysis and a genetic search based method for Android malware detection
Published 2018“…To evaluate the best features determined by GS, we used five machine learning classifiers, namely, Naïve Bayes (NB), Functional Trees (FT), J48, Random Forest (RF), and Multilayer Perceptron (MLP). …”
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Discovering optimal features using static analysis and a genetic search based method for Android malware detection
Published 2018“…To evaluate the best features determined by GS, we used five machine learning classifiers, namely, Naïve Bayes (NB), functional trees (FT), J48, random forest (RF), and multilayer perceptron (MLP). …”
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