Search Results - (( data replication learning algorithm ) OR ( variable detection path algorithm ))
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman
Published 2021“…Each technique was replicated, trained and tested accordingly. M4 competition dataset was used in this research, with 100,000 time series data and multiple data frequency, which is enough to replicate the real-world situation. …”
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IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE
Published 2017“…Selected basic behaviour-based algorithms such as wallfollower, obstacle avoidance, escape route and target detection are to be combined and its efficiency is measured. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data
Published 2019“…The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. …”
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A real-time integrated fire detection and alarm (FDA) system for network based building automation
Published 2017“…Methods/Analysis: In this work, the shortest path algorithm was chosen for series of buildings connected by a fiber-optic network. …”
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LED based NIR spectroscopy for detection of lard adulteration in palm oil via chemometrics / Katrul Nadia Basri
Published 2017“…In order to remove the uninformative variables, cumulative adaptive reweighted sampling (CARS) has been performed. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Generally, medical data is considered high-dimensional and complex data that contains many irrelevant and redundant features. …”
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Classification and quantification of palm oil adulteration via portable NIR spectroscopy
Published 2017“…In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. …”
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Classification and quantification of palm oil adulteration via portable NIR spectroscopy
Published 2024“…In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. …”
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Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices
Published 2026“…The Internet of Things (IoT) has transformed global connectivity by linking people, smart devices, and data. However, as the number of connected devices continues to grow, ensuring secure data transmission and communication has become increasingly challenging. …”
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HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text
Published 2021“…On a variety of datasets, our proposed HARC algorithm solution outperformed traditional machine learning approaches as well as comparable deep learning models by a margin of 1%. …”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers
Published 2009“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…The increasing demand for servicing codes across faculties has created a growing need for data-driven decision supports in optimizing lecturer allocation and cost efficiency. …”
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Assessment of suitable hospital location using GIS and machine learning
Published 2022“…Third, an insight into the machine learning models utilized and how their predicted weights affect hospital site suitability mapping was provided. …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
Published 2019“…This is based on highresolution Light Detection and Ranging (LiDAR) techniques both airborne and terrestrial (ALS and TLS). Different machine learning algorithms (Artificial Neural Network [ANN], K Nearest Neighbor [KNN] and Support Vector Machine [SVM]) were tested individually and with various ensemble models (bagging, voting, and boosting) to detect the probability of the landslide and rockfall occurrences. …”
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