Search Results - (( pattern extraction sensor algorithm ) OR ( data optimization method algorithm ))
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Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…Specifically, this study focuses on investigating the optimal placement of smartphones to extract tri- axis accelerometer data from the inertial sensors during stair movement. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis
Published 2022“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Undergraduates Project Papers -
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Modeling of vehicle trajectory clustering based on LCSS for traffic pattern extraction
Published 2017“…These behavioural manoeuvres are useful for interpreting the indepth study of traffic pattern in a traffic network. Hence, with the advancement of the available vehicle tracking system, vehicle trajectory dataset is selected as suitable candidate input for the traffic pattern extraction. …”
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Proceedings -
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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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Comparison Of Ridge Filters Performance in Human Vein Extraction Using 850nm Near Infrared Led Illumination
Published 2023“…The vein feature extraction algorithm is a crucial factor in the vein visualisation process. …”
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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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Integrated multichannel Young’s interferometer sensor based on long-range surface plasmon waveguides
Published 2019“…The diverging output beams from the waveguides are overlapped in the far field to form interference patterns which are then post-processed using the fast Fourier transform (FFT) algorithm to extract phase values. …”
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Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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Conference or Workshop Item -
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data
Published 2021“…Thus, this paper proposes a novel method for imputation of missing data, named KNNGOA, which optimized the KNN imputation technique based on the grasshopper optimization algorithm. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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