Search Results - (( pattern bat algorithm ) OR ((( between working algorithm ) OR ( self learning algorithm ))))
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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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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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3
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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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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Bat algorithm for rough set attribute reduction
Published 2023“…In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”
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Naive bayes-guided bat algorithm for feature selection.
Published 2013“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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9
Unsupervised monocular depth estimation with multi-scale structural similarity powered loss function / Ali Kohan
Published 2020“…Also preparing ground-truth data for a range of environments is a challenging and expensive task to accomplish. Most recent works in this context have proposed self-supervised learning approaches, where they implicitly infer the target data from a stereo pair of images and use that self-obtained target data to train a deep neural network to learn disparities of the two views from the image pair. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In this thesis the research of a self-learning algorithm will be presented, outlined and discussed in detailed manner. …”
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11
Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). The major function of the IBA is to optimize the estimated value of the three-parameters associated with the Muskingum model. …”
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Development of track-driven agriculture robot with terrain classification functionality / Khairul Azmi Mahadhir
Published 2015“…For instance, a terrain covered with gravel produces high vibration to robot when traversing on the surface. In this work, an agricultural robot is embedded with machine learning algorithm based on Support Vector Machine (SVM). …”
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13
Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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A Comprehensive Study On Developing Neural Network Models For Predicting The Coagulant Dosage And Treated Water Qualities For A Water Treatment Plant
Published 2019“…The effectiveness of the coagulant dosage and the TW quality models were improved using an imputation model and a genetic algorithm. The imputation model was developed using K-means clustering with an imputation accuracy similar to a self-organizing map, to cope with failures in hardware sensors causing downtime in fully automated water treatment plants and ensure the continual use of the coagulant dosage model. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. The second modification develops a new position update mechanism using the Bat Algorithm movement. …”
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Innovating education: AI-powered self-instructional materials for the Moodle platform
Published 2025“…Designed initially for Open and Distance Learning at Universiti Sains Malaysia, the AI-powered SIM enables self-paced and self-directed learning, catering to diverse learning needs and preferences. …”
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Contrastive Self-Supervised Learning for Image Classification
Published 2021“…Thus, people have introduced a new paradigm that falls under unsupervised learning – self-supervised learning. Through self-supervised learning, pretraining of the model can be conducted without any human-labelled data and the model can learn from the data itself. …”
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Final Year Project / Dissertation / Thesis -
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Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur
Published 2007“…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
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