Search Results - (( simulation optimization model algorithm ) OR ( using solution learning algorithm ))
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1
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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2
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The proposed DNN algorithm is structured to incorporate initial/boundary conditions in cylindrical coordinates and approximate the solution without the aid of any simulated or training data. …”
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3
Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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4
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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5
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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6
Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization
Published 2018“…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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Conference or Workshop Item -
7
Distributed learning based energy-efficient operations in small cell networks
Published 2023“…The thesis proposed a solution that employs unique characteristics of machine learning and game-theoretic framework to enable a model-free and energy-efficient small cell network. …”
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8
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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9
A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…Machine Learning (ML) is seen as a promising application that offers autonomous learning and provides optimized solutions to complex problems. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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Precision agriculture for corn using reinforcement learning
Published 2024“…Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
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Final Year Project / Dissertation / Thesis -
12
Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
Published 2005“…Time Series method has always been used in a variety of forecasting applications. In this thesis, an approach that combines the Box-Jenkins methodology for SARIMA model and Genetic Algorithm (GA) will been introduced as a new approach in making a forecast. …”
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13
A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…Then an extension, MDVRPSRC-2S, is presented as an offline two-stage SILP model of the MDDVRPSRC. These models are validated using small simulated instances with CPLEX. …”
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14
A new particle swarm optimization for wireless mesh routing protocol
Published 2008“…The Particle swarm optimization is based on a social-psychological model of social influence and social learning for finding optimal regions of search space in particles population. …”
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Monograph -
15
Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath.
Published 2001“…Most of the developed commercial CFD (Computational Fluid Dynamics) packages do not attempt to document (or don’t want to publish !!) the detailed algorithm for parallelising the code; even the ordinary solution strategies are tedious to learn sometimes. …”
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16
Precision agriculture for corn using reinforcement learning
Published 2024“…Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
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Final Year Project / Dissertation / Thesis -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
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Deep learning-based item classification for retail automation
Published 2025“…The CNN model was optimized for both accuracy and speed, incorporating regularization techniques such as dropout and batch normalization. …”
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Final Year Project / Dissertation / Thesis -
19
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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20
EDITORIAL: INTEGRATION OF HYDROLOGICAL MODELS AND MACHINE LEARNING TECHNIQUES FOR WATER RESOURCES MANAGEMENT
Published 2025“…Advancements in computational power and data availability enable machine learning to complement traditional models. Algorithms such as ANNs, SVMs, and RF enhance hydrological forecasting, while deep learning methods (LSTMs, CNNs) improve spatio-temporal predictions. …”
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