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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Text Extraction Algorithm for Web Text Classification
Published 2010“…This study provides a text extraction algorithm for web text classification. The extraction algorithm consists of three phases namely web page extraction, rule formulation, and algorithm validation. …”
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A protocol for developing a classification system of mosquitoes using transfer learning
Published 2022“…Transfer learning is a type of machine learning that is viable and durable in image classification with limited training images. This protocol aims to develop step-by-step procedure in developing a classification system with transfer learning algorithm for mosquito, we demonstrate the protocol to classify two species of Aedes mosquito - Aedes aegypti L. and Aedes albopitus L, but user can adopt the protocol for higher number of species classification. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…Presently, the classification accuracy of the assessment is proportional to the size of the data. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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Joint routing protocol and image compression algorithm for prolonging node lifetime in wireless sensor network
Published 2018“…Thus the proposed algorithm prolongs the network under consideration by 57 – 62% as compared to networks with conventional routing protocols.…”
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10
Detection algorithm for internet worms scanning that used user datagram protocol
Published 2024journal::journal article -
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Classification model for predictive maintenance of small steam sterilisers
Published 2020“…The classification models were built from multisensory data, obtained from 1000 protocol records of CertoClav Vacuum Pro steam sterilisers. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Internet of Things (IoT) based activity recognition strategies in smart homes: a review
Published 2022“…They often communicate using appropriate protocols such as MQTT, CoAP, or HTTP to ensure the smooth transmission of data used by a variety of smart home services. …”
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Data redundancy reduction scheme for data aggregation in wireless sensor network
Published 2020“…This research proposes Data Redundancy Reduction Scheme (DRRS) which includes three algorithms namely, Metadata Classification (MC), Selection Active Nodes (SAN) and Anomaly Detection (AD) algorithms that works before data aggregation, when multiple composite events simultaneously occur in the different locations within the cluster. …”
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Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability
Published 2022“…The first phase aims to investigate the best types of required data, features and algorithms to be used in the final proposed methodology to predict exact EDSS, and different ranges of EDSS. …”
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Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems
Published 2019“…It supervises physical process by collecting data from sensors and performs monitoring, data logging, alarm and diagnostic functions. …”
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EEG-based emergency calling system for neurological disorder patient
Published 2025“…The MATLAB Graphical User Interface (GUI) algorithm is constructed to display the EEG data analysis and health status of the Neurological disorder patients. …”
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Prediction of sleep pattern for university students using machine learning
Published 2026“…The Random Forest algorithm was employed for classification, evaluated using a 5-Fold Cross-Validation protocol, and achieved an average accuracy of 81.46%. …”
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Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab
Published 2015“…The methodology presented in this research consisted of several stages namely, image acquisition, image segmentation, feature extraction/selection and, classification. The data was collected from two different sources, University of Malaya Medical Center (UMMC), Malaysia and M. …”
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