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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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2
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…Two new adaptive routing algorithms named Enhanced Confidence-based Q (ECQ) and Enhanced Confidence-based Dual Reinforcement Q (ECDRQ) Routing Algorithms are proposed in this thesis. …”
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4
One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…Hence, this indicates that Invasive Weed Optimization could be implemented as a new learning algorithm for an Artificial Neural Network.…”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Book Section -
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems
Published 2015“…In this paper, a new design strategy is presented where variable operating conditions, which better represent real-world problems, are considered. …”
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Network game (Literati) / Chung Mei Kuen
Published 2003“…Java applet is a well-known and widely used example of mobile code (a variation on the traditional client-server model). …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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A bayesian network approach to identify factors affecting learning of Additional Mathematics
Published 2015“…Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. …”
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
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IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE
Published 2017“…When the environment is changed the algorithm may fail to adapt itself to the new configuration. …”
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Final Year Project -
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider
Published 2011“…The studies show beyond technical algorithms, physical aspects plays a big rule in client server model. …”
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17
A hybridisation of adaptive variable neighbourhood search and large neighbourhood search: Application to the vehicle routing problem
Published 2016“…In this paper, an adaptive variable neighbourhood search (AVNS) algorithm that incorporates large neighbourhood search (LNS) as a diversification strategy is proposed and applied to the capacitated vehicle routing problem. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…This study contributes to the field by proposing a new regularization technique, demonstrating the effectiveness of the Algorithm Adaptation framework, and providing insights into the associations between diabetes complications. …”
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