Search Results - (( data optimization method algorithm ) OR ( data navigation learning algorithm ))
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…This research contributes novel insights into the application of clustering algorithms in banking, proposing pragmatic solutions for efficient data analysis and campaign optimization. …”
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Deep Reinforcement Learning For Control
Published 2021“…As a consequence, the agent is expected to have trained behaviors and navigation without crashing. The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm
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Conference or Workshop Item -
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Improvement of an integrated global positioning system and inertial navigation system for land navigation application
Published 2012“…In addition, in this work a GPS predictor is developed to incorporate information from the accelerometers and gyroscopes at high rates and information from GPS measurements at low rates to improve the vehicle strapdown inertial navigation system (SDINS) with the aid of GPS. This work also presents a new method for de-noising the GPS and INS data and estimate the INS error using wavelet multi-resolution analysis algorithm (WMRA) based particle swarm optimization (PSO) with a well designed structure appropriate for practical and real time implementations due to its very short optimizing time and elevated accuracy. …”
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Challenges in supervised and unsupervised learning: a comprehensive overview
Published 2024“…In unsupervised learning, difficulties encompass issues like overfitting, choosing the appropriate algorithm, and interpreting results. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
Published 2023“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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A Review: Current Trend of Immersive Technologies for Indoor Navigation and the Algorithms
Published 2024“…Based on the findings of this review, we can conclude that an efficient solution for indoor navigation that uses the capabilities of embedded data and technological advances in immersive technologies can be achieved by training the shortest path algorithm with a deep learning algorithm to enhance the indoor navigation system.…”
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Advancing mobile robot navigation with DRL and heuristic rewards: a comprehensive review
Published 2025“…The advent of Deep Reinforcement Learning (DRL) has spurred significant research into enabling mobile robots to learn effective navigation by optimizing actions based on environmental rewards. …”
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Supervisory fuzzy learning control for underwater target tracking
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The performance of MANFIE was compared with existing methods in a diversity of practical benchmark applications such as pattern classifications, time series predictions, modeling with inverse learning control and mobile robot navigation. The MANFIE has shown the ability to reduce and form the robust minimal rules (Rules reduced on average 97.95% and 96.90% accuracy for pattern classifications, rules reduced on average 97.15%, 75% and 98.43% for time series predictions, modeling with inverse learning control and mobile robot navigation respectively) to make an appropriate structure and minimize the root mean square error (RMSE - 0.024, 0.149 for time series predictions, 0.007 for modeling with learning control, 0.027 for mobile robot navigation) with the best accuracy. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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