Search Results - (( data machine learning algorithm ) OR ( parameter optimization sensor algorithm ))
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023“…Battery management systems; Charging (batteries); Data handling; Decision trees; Digital storage; Electric vehicles; Learning algorithms; Lithium-ion batteries; Machine learning; Differential search algorithm; Electric vehicle batteries; Lithium ions; Lithiumion battery; Random forest regression; Random forests; Regression algorithms; Search Algorithms; State-of-charge estimation; States of charges; Regression analysis…”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024Subjects:Article -
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Water quality monitoring using machine learning and IoT: a review
Published 2024“…The paper explores various ML algorithms, including supervised and unsupervised learning and deep learning, along with their applications, and discusses the use of IoT sensors for real-time monitoring of water quality parameters such as pH, dissolved oxygen, temperature, and turbidity.…”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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Water optimization technique for precision irrigation system using IoT and machine learning
Published 2022“…The cloud environment is used to store the observed parameters from the IoT components. The machine learning algorithm is useful in taking the process of data, from the cloud environments, and do forecasting on the irrigation system. …”
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Smart waste management system with IoT monitoring
Published 2023“…Through advanced data analytics and machine learning algorithms, the platform predicts waste accumulation patterns, optimizes collection routes, schedules pickups based on fill-level data, and detects any abnormal conditions. …”
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Automatic nutrient mixer and pH Level for hydroponic application / Hariz Akmal Azizan
Published 2024“…Future work could involve integrating advanced machine learning algorithms to optimize nutrient dosing and implement self-harvesting mechanisms, thereby enhancing plant production and contributing to the development of more efficient and sustainable hydroponic systems for agricultural practices.…”
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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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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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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…Imbalanced data is one of the challenges in a classification task in machine learning. …”
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Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms
Published 2019“…Hence, the mapping of oil palm distributions via machine learning algorithm was better than that via non-machine learning algorithm.…”
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Impact learning: A learning method from feature's impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid
Published 2022“…The methodology includes drive test measurement for data collection, exploratory data analysis, data preparation, and applying machine learning algorithms to predict mobile network performance. …”
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…Machine learning is the study of computer algorithms that can automatically improve based on data and experience. …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin
Published 2022“…Then, the outcomes demonstrated that the best classifier for categorizing our data with 0.96% accuracy is the Decision Tree machine learning algorithm. …”
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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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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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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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