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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…Exploratory Data Analysis (EDA) highlights the class imbalance problem in detecting fake jobs, which tends the model to act aggressively toward the minority class. …”
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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…”
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An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
Published 2019“…Also, it is possible that the attack is not directly detected. Hence, this highlights the need for an algorithm that is capable of assessing the widespread damage scale before starting the repair of the inconsistent medical database. …”
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Cutting‐edge technologies for detecting and controlling fish diseases: Current status, outlook, and challenges
Published 2024“…Here, we highlighted the potential of machine learning algorithms in early pathogen detection and the possibilities of intelligent aquaculture in controlling disease outbreaks at the farm level. …”
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
Published 2020“…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …”
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VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems
Published 2019“…The Nonnested Generalized Exemplars (NNGE) algorithm is one of the most accurate classification techniques that can work with such data of CPPS. …”
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
Published 2021“…<p dir="ltr">In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but query analysis and mobile data security are major issues. Several research works have been made on efficient detection of antipatterns for minimizing the complexity of query analysis. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. …”
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A data envelopment analysis model for opinion leaders’ identification in social networks
Published 2024“…Social Network Analysis (SNA)-based OLs finding methods deal with a considerable amount of data due to using entire relationships between all of the users in a network, which makes the algorithms time-consuming. …”
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Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents
Published 2019“…It was observed that the linear classification algorithm was not able to detect heart attack in noisy data, whereas the support vector machine (SVM) algorithm with polynomial kernel with extended time–frequency features using extended modified B-distribution (EMBD) showed highest accuracy and was able to detect 97.4% and 96.3% of ST-elevation myocardial infarction (STEMI) and non-ST-elevation MI (NSTEMI), respectively. …”
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Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022“…Nevertheless, the GOA is unsuitable for addressing multimodal, hybrid functions, and data mining problems. Therefore, the current paper proposes the orthogonal learning (OL) method with Rosenbrock’s direct rotation strategy to improve the GOA and sustain the solution variety (IGOA). …”
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…<p>This paper proposes a novel fault detection and diagnosis (FDD) technique for grid-tied PV systems. …”