Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark حسب 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. …"

Improved Machine Learning for Multiclass Fault Classification in Industrial Processes حسب Khaled Dhibi (16891524)

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

"…The proliferation of smart meters in the grids has resulted in an explosion of energy datasets. Processing such data is challenging and usually takes a longer time than the requirement of a short-term load forecast. …"

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

"…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …"

Sulfur oxidative coupling of methane process development and its modeling via machine learning حسب Giovanni Scabbia (13751501)

"…The outcomes of the simulated process were used to design a data-driven modeling approach, based on machine learning methods, and to evaluate its interpolation accuracy. …"

Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing حسب Jincheng Zhou (1887307)

"…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. …"

On the Use of Deep Learning for Video Classification حسب Atiq ur Rehman (14153391)

Regression estimation for continuous-time functional data processes with missing at random response حسب Mohamed Chaouch (17983846)

Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods حسب Arash Golabi (21841484)

Optimizing malicious website prediction: An advanced XGBoost-based machine learning model حسب Sumaira Hussain (19259669)

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval حسب Mohammed Tahar Habib Kaib (21633176)

An Empirical Analysis of NMT-Derived Interlingual Embeddings and Their Use in Parallel Sentence Identification حسب Cristina Espana-Bonet (19720063)

"…</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Journal of Selected Topics in Signal Processing<br>License:<a href="https://creativecommons.org/licenses/by/4.0/" rel="noreferrer" target="_blank"> https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/jstsp.2017.2764273" target="_blank">https://dx.doi.org/10.1109/jstsp.2017.2764273</a></p>…"

Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

"…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"

Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model حسب Dabeeruddin Syed (16864260)

"…In the model-building phase, the hybrid model is trained on the processed data. The hybrid deep learning (DL) model is based on the stacking of fully connected layers, and unidirectional Long Short Term Memory (LSTMs) on bi-directional LSTMs. …"

Deep learning-based marine big data fusion for ocean environment monitoring: Towards shape optimization and salient objects detection حسب Sulaiman Khan (12585349)

Assessing the risk of vibration-induced fatigue in process pipework using convolutional neural networks حسب Ahmed Mohamed (628889)

"…In contrast, vibration data can be efficiently collected using accelerometers and single-channel data loggers, providing a more feasible solution for initial screening. …"

A Comparative Study of Contemporary Learning Paradigms in Bug Report Priority Detection حسب Eyüp Halit Yilmaz (21400700)

An efficient approach for textual data classification using deep learning حسب Abdullah Alqahtani (7128143)

"…This paper employs machine and deep learning techniques to classify textual data. Textual data contains much useless information that must be pre-processed. …"

Exploring the potential of onboard energy scavenging subsystems for generating valuable data حسب Raziq Yaqub (16488878)

RDFFrames: knowledge graph access for machine learning tools حسب Aisha Mohamed (5152970)

"…Machine learning tools work on data in tabular format and process it using an imperative programming style, while SPARQL is declarative and has as its basic operation matching graph patterns to RDF triples. …"