A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

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Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. …”

Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

Subjects: “…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…”
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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

“…Statistical analysis and machine learning can play a vital role in detecting the anomalies in the data, which enhances the security level of the smart home IoT system which is the goal of this paper. …”

On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…<p>Machine learning algorithms have been intensively applied to perform load forecasting to obtain better accuracies as compared to traditional statistical methods. …”

Development of an Optimization Algorithm for Internet Data Traffic by Misbahuddin, Syed

“…In this paper, an optimization algorithm is proposed to reduce net data traffic, which works at Internet layer in the TCP/IP reference model. …”
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

“…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …”
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A Tabu Search algorithm for mapping data to multicomputers. (c1997) by Diab, Kamal M.

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A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

“…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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Allocating data to distributed-memory multiprocessors by genetic algorithms by Mansour, Nashat

“…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …”
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Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects by Mohamed Massaoudi (16888710)

“…Further, we taxonomically delve into the mechanism behind some of the trending DL algorithms. We then showcase the DL enabling technologies in SG, such as federated learning, edge intelligence, and distributed computing. …”

Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

“…This study aims to classify the highest 50 global smart cities based on key livability and technology indices, using advanced <u>machine learning</u> (ML) models to assess city performance comprehensively. …”

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

“…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. The most widely used algorithms incorporate Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN), and MobileNet with accuracy rates between 64.3 and 100%. …”

Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)