Search Results - (( parameter optimization sensor algorithm ) OR ( _ localization path algorithm ))
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Modelling of multi-robot system for search and rescue
Published 2023“…Moreover, to cope with dynamic environments, a combination of global and local path planning methods is introduced. The PSO algorithm functions as a global path planner, determining the complete path for each robot, whereas a sensor-based obstacle avoidance algorithm serves as a local planner to avoid collision with dynamic obstacles during navigation. …”
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Final Year Project / Dissertation / Thesis -
2
A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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Thesis -
3
Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm
Published 2015“…The exploration algorithm should perform fast localization of sensor nodes in energy efficient manner. …”
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Thesis -
4
FuMAM: fuzzy-based mobile agent migration approach for data gathering in wireless sensor networks
Published 2018“…Moreover, the proposed FuMAM approach outperforms the compared algorithms in terms of energy distribution usage among nodes.…”
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Article -
5
Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper
Published 2017“…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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Article -
6
Parameter adaptation for ant colony system in wireless sensor network
Published 2019“…The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). …”
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Article -
7
DC-based PV-powered home energy system
Published 2017“…The controller algorithm requires also the variation range of the geographical weather parameters (irradiance and temperature) to specify the MPP which is equivalent to that operating voltage at minimum weather parameters. …”
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Thesis -
8
Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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9
Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali
Published 2024“…The IDBA-AFW evaluates the fitness of relay nodes based on multiple criteria, such as energy efficiency, throughput, and end-to-end delay. Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
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Thesis -
10
Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
Published 2021“…In this work, these parameters are optimized using dynamic inertia weight artificial bees colony (DIW-ABC) optimization algorithm. …”
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Conference or Workshop Item -
11
A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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Thesis -
12
Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…Path planning (PP) together with mapping and localization are important elements in autonomous mobile robot navigation systems. …”
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Thesis -
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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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Multi-robot path planning based on the improved nutcracker optimization algorithm and the dynamic window approach
Published 2024“…This paper proposes a multi-robot path planning algorithm that integrates the improved nutcracker optimization algorithm with the improved dynamic window approach. …”
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Article -
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Enhanced path planning for industrial robot: integrating modified artificial potential field and A* algorithm / Fan Rui ... [et al.]
Published 2024“…The study analyses the principles and limitations of classical algorithms. The study introduces a modified APF algorithm to address issues of local minima and path oscillation, which is integrated with A* to guide movement towards the virtual target. …”
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17
A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The image processing includes several operations to apply GLS on the prepared local map. The proposed algorithm generates the path within the prepared local map to find the path between start-to-goal positions to avoid obstacles and adhere to constraints. …”
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Thesis -
18
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”
Article -
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. …”
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Thesis -
20
Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. …”
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