Search Results - (( site selection means algorithm ) OR ( wave optimization path algorithm ))*
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1
A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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Thesis -
2
A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance
Published 2022“…An optimal path between the start and target point is found by forming a wave of points in all directions towards the target position considering target minimum and border maximum distance principles. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2021“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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4
Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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5
Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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6
Development of a State-Space Observer for Active Noise Control Systems
Published 2009“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Thesis -
7
Levy slime mould algorithm for solving numerical and engineering optimization problems
Published 2022“…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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Conference or Workshop Item -
8
Efficient and scalable ant colony optimization based WSN routing protocol for IoT
Published 2020“…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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Efficient relay placement algorithm using landscape aware routing (erpalar)
Published 2011“…ERP ALAR was implemented in Matlab R2009a using Genetic Algorithm (GA) with multi-objectives. GA is an optimization algorithm that simulates natural selection process as found in nature. …”
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Thesis -
11
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Three algorithms of Linear (PURELIN), hyperbolic tangent sigmoid (TANSIG) and logistic sigmoid (LOGSIG) activation functions were selected for output layer. …”
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12
Modelling the yield loss of oil palm due to Ganoderma Basal Stem Rot disease
Published 2016“…The predictive performance of the three best models which represent three different model building algorithms were assessed and compared. Based on mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), BMA model has the lowest values, thus selected as the best model for oil palm yield loss. …”
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13
Modelling the yield loss of oil palm due to ganoderma basal stem rot disease
Published 2016“…The predictive performance of the three best models which represent three different model building algorithms were assessed and compared. Based on mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), BMA model has the lowest values, thus selected as the best model for oil palm yield loss. …”
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Thesis -
14
Assessment of suitable hospital location using GIS and machine learning
Published 2022“…First, the conditioning factors were optimized and ranked to identify and select the most correlated factors to predict the suitability of a hospital site by applying the correlation feature selection (CFS) algorithm and the greedy-stepwise search method. …”
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15
Reliability of voxel gray values in cone beam computed tomography for preoperative implant planning assessment
Published 2012“…In all the selected ROIs, CBCT showed higher mean values than MSCT. …”
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Molecular docking studies of Pyranose-2-oxidase from trametes multicolor
Published 2013“…Lamarckian genetic algorithm (LGA) is used to search for active sites and potential mean force (PMF) scoring method is used to evaluate different binding sites. …”
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Proceeding Paper -
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Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System
Published 2010“…Results are obtained from one hidden layer neural network and two hidden layers neural network structures, for both adopted algorithms. Comparisons have been made between the results from the two algorithms based on the Root Mean Square Error. …”
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Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model
Published 2023“…Thus, this study attempts to fill the gap by proposing a feature drift-aware algorithm for detecting the evolved XSS attacks. The proposed approach is a dynamic feature selection based on a deep Q-network multi-agent feature selection (DQN-MAFS) framework. …”
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Development Of Construction Noise Prediction Method Using Deep Learning Model
Published 2021“…The mean absolute errors (0.2 to 0.25), root mean square errors (0.3 to 0.42), and explained variance scores (0.9975 to 0.9988) of the selected best deep learning models indicate an incredibly accurate, fewer outliers, and extraordinarily reliable noise prediction model. …”
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Final Year Project / Dissertation / Thesis -
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Modification and characterization of phytase for animal feed production
Published 2009“…Automated docking based on genetic algorithm is used to dock the phytate in the active site and Partial Mean Force (PMF) scoring is used to calculate the strength of the binding before and after mutation.…”
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