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1
Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks
Published 2012“…Finally, we propose Self-Decision Route Selection scheme which is an improvement of the Hop-based Spanning Tree (HST) algorithm that is used in some routing protocols such as AODV and DSR. …”
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2
Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks
Published 2015“…Simulation results show that the proposed algorithm converges and outperforms a source based tree algorithm. …”
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Proceeding Paper -
3
Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…The simulation of planting lining design relative to possible solutions of dividing an area to blocks (block division) and selecting planting lining direction towards optimizing tree planting areas is a complex problem. …”
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4
A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. …”
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Online PID controller tuning using tree physiology optimization
Published 2017“…This iterative correlation leads towards optimum solution. A simulation of online PID-tuning is applied to demonstrate the effectiveness of proposed algorithm and compared with other optimization method which are Particle Swarm Optimization (PSO) and Ziegler-Nichols (Z-N) method. © 2016 IEEE.…”
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7
An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms
Published 2022“…In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. The simulation results established the findings that Bagged Trees, Fine Trees, and Medium Trees are, respectively, the best-, second-best-, and third-best-performing algorithms in terms of efficacy. …”
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8
Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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9
Tree physiology optimization on SISO and MIMO PID control tuning
Published 2018“…This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using tree physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). …”
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A safe overtaking control scheme for autonomous vehicles using rapid-exploration random tree
Published 2022“…Firstly, the kinematics and dynamic model of the vehicle are implemented. Secondly, the RRT algorithm and the A-star algorithm are expounded, and the idea of the A-star algorithm is applied to the RRT algorithm for improvement. …”
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Proceedings -
12
Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm
Published 2015“…Developing an exploration algorithm based on spanning tree is the main contribution. …”
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13
Application of sampling-based motion planning algorithms in autonomous vehicle navigation
Published 2016“…The proposed method provides near-optimal solutions with smaller trees and in lower running time.…”
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Book Section -
14
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…It is attained successfully by combining the mean in K-Means algorithm, minimum and maximum in K-Midranges algorithm and compute their average as mean cluster of Hybrid mean. …”
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15
Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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16
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker
Published 2011“…And the second algorithm is the optimization technique for indoor wireless coverage. …”
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18
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Thesis -
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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