Search Results - (( developing state sensor algorithm ) OR ( java application stemming algorithm ))
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In the simulation the robot is equipped with thirteen distance sensing sensors. From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Design and development of cooperative simultaneous localization and mapping integrated with neural network for mobile robot
Published 2024“…From the results, it can be concluded that the development of CSLAM algorithm integrated with ANN able to improve the performance of CSLAM for mobile robot using low-cost sensor.…”
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Development of multi-input sensor algorithm for autonomous underwater vehicle (AUV) system stage 2
Published 2010“…The sensors implemented in AUV such as vision system, hydrophone system and sonar system successful develop in stage one. …”
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A distributed particle filtering approach for multiple acoustic source tracking using an acoustic vector sensor network
Published 2015“…Different centralized approaches such as least-squares (LS) and particle filtering (PF) algorithms have been developed to localize an acoustic source by using a distributed acoustic vector sensor (AVS) array. …”
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Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory
Published 2015“…Finally, the algorithm to obtain a general FTCS framework is developed to provide compensation of the sensor faults through the introduction of a new control law unto the existing nominal one. …”
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Random traveling wave pulse coupled oscillator (RTWPCO) algorithm of energy-efficient wireless sensor networks
Published 2018“…In addition, the mechanism improves the data gathering ratio by up to 70% and 68%, respectively. This is due to the developed technique helps to reduce the high consumed energy in the sensor network and increases the data collection throughout the transmission states in wireless sensor networks.…”
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Development of a wireless mesh network routing algorithm for oil and gas pipeline networks
Published 2021“…The purpose of this research is to develop an enhanced routing algorithm suitable for oil and gas pipeline application in the refinery area. …”
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Application of machine vision systems in aquaculture with emphasis on fish: state-of-the-art and key issues
Published 2025“…This review showed that MVSs and optical sensors have found real-world application based on tremendous possibility offered by digital camera development and increasing the speed of computer-based processing; however, still new algorithms, methods and re-engineered sensors need to be developed to meet real-world requirements.…”
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Evaluation of a spacecraft attitude and rate estimation algorithm
Published 2010“…Purpose: This paper aims to present the development and performance evaluation of an attitude and rate estimation algorithm using an extended Kalman filter structure based on a body‐referenced representation of the state. …”
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Developing A Control Protocol Algorithm For Stimulating The Street Light System
Published 2017“…Thus, smart protocol algorithm is developed to replace the previous system. …”
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Designated Path Routing Algorithm For Dense Wireless Sensor Network
Published 2021“…The proposed algorithm has been developed to optimize the network performance by dividing the traffic into two and by reducing the flooding during route discovery. …”
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An analysis of state covariance of mobile robot navigation in unstructured environment based on ROS
Published 2021“…ROS is a framework to develop robotic application and it consists of algorithms to build maps, navigate, and interpret sensor data. …”
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Trade-off between energy efficiency and collisions for MAC protocols of wireless sensor network
Published 2015“…Simulation models have been developed and simulated to verify the performance improvements of the proposed algorithms. …”
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Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…Data collection experiments yield a diverse dataset of hand gestures, including variations in speed, essential for algorithm development. The developed algorithms interpret raw IR-UWB radar sensor data and associate it with specific hand gestures, addressing the core objective of gesture recognition. …”
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Estimation of electric vehicle turning radius through machine learning for roundabout cornering
Published 2021“…This paper presents an alternative approach for estimating the turning radius using machine learning technique. While on-board sensors are unable to offer adequate information on vehicle states to the algorithm, vehicle states other than those directly detected by on-board sensors can be inferred using machine learning (ML) approaches based on the collected data. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…There has been much previous research developing new methods to improve accuracy of Traffic State Prediction (TSP) which are designed according to its advantage for static sensors such as video cameras, inductive loop detectors and other static sensors. …”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023Conference Paper -
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Coverage and connectivity maximization for wireless sensor networks using improved chaotic grey wolf optimization
Published 2025“…Similarly, in Case 3, with 40 sensor nodes, the coverage rate is 91.6875%, and in Case 4, with 50 sensor nodes, it is 99.4940%. …”
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