Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) حسب Tay, Bilal M.

"…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

Scatter search metaheuristic for homology based protein structure prediction. (c2015) حسب Stamboulian, Mouses Hrag

"…The 3D models predicted by our algorithm show improved root mean standard deviations (RMSD) with respect to the native structures.…"
احصل على النص الكامل
احصل على النص الكامل

Stability and Numerical Solutions of Second Wave Mathematical Modeling on COVID-19 and Omicron Outbreak Strategy of Pandemic: Analytical and Error Analysis of Approximate Series So... حسب Ashwin Muniyappan (19570051)

"…<p dir="ltr">This paper deals with the mathematical modeling of the second wave of COVID-19 and verifies the current Omicron variant pandemic data in India. …"

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma حسب Rawan AlSaad (14159019)

"…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …"

Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis حسب Sami Elzeiny (16891521)

"…This work leverages the output of wearable technology to provide automatic stress and stressor identification model. In particular, this study proposes a novel algorithm that first detects instances of stress and then classifies the stressor type using photoplethysmography (PPG) data from wearable smartwatches. …"

Adaptive Video Streaming Over Cognitive Radio Networks حسب Mohamed, Ala Eldin Omer

احصل على النص الكامل

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes حسب Muhammad Mohsin Khan (22150360)

"…Feature selection was done using a Random Forest algorithm to identify the top 20 features for the SAH severity prediction. …"

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... حسب Tarik Elhadd (5480393)

"…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…"

Transmission Line Fault Location Using Unsynchronized Measurements حسب Hussain, Shoaib

احصل على النص الكامل

Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series حسب Lasfer, Assia

احصل على النص الكامل

The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review حسب Zainab Jan (17306614)

"…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …"

Deep and transfer learning for building occupancy detection: A review and comparative analysis حسب Aya Nabil Sayed (17317006)

"…Besides, integrating artificial intelligence (AI) into the BIoT is essential for data analysis and intelligent decision-making. Thus, data-driven approaches to infer occupancy patterns usage are gaining growing interest in BIoT applications. …"

Ensemble Deep Random Vector Functional Link Neural Network for Regression حسب Minghui Hu (2457952)

"…The esc-edRVFL is identified as the best-performing algorithm through a comprehensive evaluation of 31 UCI datasets.…"

Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks حسب Mohamed Massaoudi (16888710)

"…In a postfault scenario, a copula of processing blocks is implemented to ensure the reliability of the proposed method where high-importance features are incorporated into the TCN-GWO model. The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …"

A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation حسب Reem Tluli (22282702)

"…By thoroughly reviewing the existing literature and methodologies, this paper provides a comprehensive overview of the approaches used in ambulance allocation, routing, demand estimation and simulation models. We discuss the challenges faced by these methods, emphasizing the need for innovative solutions that can adapt to real-time data and changing emergency patterns. …"

Framework for rapid design and optimisation of immersive battery cooling system حسب Ali Almshahy (23544823)

"…A conjugate heat transfer model for a 3S2P pouch cell module (20 Ah LiFePO₄) is developed and validated against experimental data (< 2% error). …"

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas حسب Marwan Dhuheir (19170898)

"…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …"

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…"

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects حسب Mohamed Massaoudi (16888710)

"…This ongoing transition undergoes rapid changes, requiring a plethora of advanced methodologies to process the big data generated by various units. In this context, SG stands tied very closely to Deep Learning (DL) as an emerging technology for creating a more decentralized and intelligent energy paradigm while integrating high intelligence in supervisory and operational decision-making. …"

Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method حسب Mohamed Massaoudi (16888710)

"…The proposed model is thoroughly assessed through an empirical study using a real data set from Australia. …"