Search Results - (( using solution learning algorithm ) OR ( using notification based algorithm ))
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A real-time mobile notification system for inventory stock out detection using SIFT and RANSAC
Published 2020“…The proposed method is a machine learning based real-time notification system using the exciting Scale Invariant Feature Transform feature detector (SIFT) and Random Sample Consensus (RANSAC) algorithms. …”
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An indoor based push notification for location-based marketing using bluetooth smart ready technology / Nur Farehah Alias
Published 2017“…Therefore, this project has proposed a method called token based alert notification. There are three algorithm developed for token based alert notification which is tokenization algorithm, token matching algorithm and item identification algorithm. …”
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Enhancement load balancing in failover web server by using HTTP-response status techniques with pfsense opensource / Muhammad Hafiz Ramli
Published 2020“…Increasing the number of failures causes the number of failures of successfulness rate in ICMP based and congestion in HTTP based monitoring. Meanwhile, an email notification was introduced in ICMP and HTTP based monitoring as a notification to the administrator when the failure occurs.…”
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Wet diaper detection and notification device to alert the baby caretaker
Published 2022“…Skin rashes can occur when the diaper is wet with urine and left to be used for a long time with the baby. This paper aims (i) to develop wet diaper detection and notification device for helping caretakers identify wet diaper conditions, (ii) to evaluate the performance of the wet diaper detection and notification device based on the response time to trigger notification after detecting wet diaper condition. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…The CDRQ Routing Algorithm provides a solution to the problem addressed above by integrating the advantages of CQ Routing Algorithm and Dual Reinforcement Learning. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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Proceeding Paper -
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Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language
Published 2019“…Computational thinking or CT refers to the thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer. …”
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Algorithm as a problem solving technique for teaching and learning of the Malay language
Published 2019“…Computational thinking or CT refers to the thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer. …”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…It was shown that our proposed model exhibits stronger search ability compared to other metaheuristic algorithms and Exhaustive Search. Our model enhanced the efficiency of the learning phase, resulting in the number of global solutions accounting for 100 %, and significantly improved the global solution diversity. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications
Published 2020“…The solution provided by deep learning for a differential equation is in a closed analytical form which is differentiable and could be used in any subsequent computation. …”
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Conference or Workshop Item -
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Application of the bees algorithm for constrained mechanical design optimisation problem
Published 2019“…To find the optimal solution for the multiple disc clutch design, the Bees Algorithm will be used and expected to give better result compared to other optimisation algorithms that already have been used.…”
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TRIP PLANNER MOBILE APPLICATION FOR SARAWAK TOURIST WITH USING INTELLIGENT AGENT BASED DECISION MAKING ALGORITHMS
Published 2020“…Thus, the proposed system which is trip planner mobile application for Sarawak tourist with using intelligent agent based decision making algorithms may help to resolve the problem. …”
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Final Year Project Report / IMRAD -
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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