Search Results - (( java application max algorithm ) OR ( using (gamification OR modification) learning algorithm ))
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Open access for gamification: a systematic review of literature across disciplines
Published 2020“…With the increasing need for developing effective learning methods, gamification has been widely used as a tool to improve the desire and interest in learning. …”
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Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…To address these problems, this research proposes three new distributed static batch mode inspired algorithms. The first (proposed) algorithm is based on Min-Min, called Min-Diff, the second algorithm is based on Max-Min, called Max-Average, and the third algorithm is to handle the load balancing, called Efficient Load Balancing (ELB). …”
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Gamification of Regional Tourism Engagement: Analysis and Design of a Web-Based Information System
Published 2025“…The system integrates a structured gamification algorithm with a scalable relational database model, built using React.js and Firebase, to ensure responsive and consistent user experiences. …”
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Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
Published 2016“…The knowledge will be stored, used, referred, postulated and reasoned with. Those activities define learning in its own specific domain and context. …”
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A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications
Published 2025“…Among the applied machine learning algorithms, the XGBoost ensemble model using the tenfold cross-validation test achieved improved results than existing state-of-the-art models. …”
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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“…Over the years, many improvements and modifications of the back propagation learning algorithm have been reported. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Learning to filter text in forum message
Published 2005“…In this paper, the modification of the algorithm including pre-processing and classification will be discussed in the attempt to apply learning to filter forum messages.…”
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Three-term backpropagation algorithm for classification problem
Published 2006“…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Furthermore, the results revealed a high convergence rate, upon which the algorithm’s performance was subjected to data clustering problems and investigated using six real datasets. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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Grammar-based prosody modification for explicit control Malay language storytelling speech synthesis / Muhammad Izzad Ramli
Published 2018“…Using Harmonic Noise Model (HNM) as the synthesizer, the grammar-based prosody modification rules are used to produce the synthesized storytelling speech. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…By considering these limitations, two modifications were made upon the conventional MVO in our proposed mMVO algorithm. …”
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