A comparative study on ensemble soft-computing methods for geothermal power production potential forecasting

R Kenanoğlu, İ Mert, C Baydar, Ö Köse, H Yağlı - Energy, 2024 - Elsevier
Many developed countries are increasingly interested in renewable energy sources (RESs)
as a result of environmental changes and the depletion of fossil fuels in recent years. Since …

The intersection of machine learning with forecasting and optimisation: theory and applications

M Abolghasemi - Forecasting with Artificial Intelligence: Theory and …, 2023 - Springer
Forecasting and optimisation are two major fields of operations research that are utilised to
deal with uncertainties and to make the best decisions. These methods are widely used in …

Predicting the Solution Time for Optimization Problems Using Machine Learning: Case of Job Shop Scheduling Problem

S Pouya, O Toragay, M Mohammadi - International Conference on …, 2023 - Springer
In organizations that use optimization and other computer-related problem-solving
techniques, a better understanding of the required computational time is essential for …

How to predict and optimise with asymmetric error metrics

M Abolghasemi, R Bean - arxiv preprint arxiv:2211.13586, 2022 - arxiv.org
In this paper, we examine the concept of the predict and optimise problem with specific
reference to the third Technical Challenge of the IEEE Computational Intelligence Society. In …

Digital Twins for forecasting and decision optimisation with machine learning: applications in wastewater treatment

M Colwell, M Abolghasemi - arxiv preprint arxiv:2404.14635, 2024 - arxiv.org
Prediction and optimisation are two widely used techniques that have found many
applications in solving real-world problems. While prediction is concerned with estimating …

[HTML][HTML] EcD-Net: Encoder-Corollary Atrous Spatial Pyramid Pooling-decoder network for automated pancreas segmentation of 2D CT images

IB Senkyire, KK Gedeon, E Freeman… - Informatics in Medicine …, 2024 - Elsevier
Automatic pancreas segmentation of CT scans enables physicians to identify and monitor
the abnormalities in the pancreas. This facilitates intraoperative assistance, surgical …

Approximating Solutions to the Knapsack Problem Using the Lagrangian Dual Framework

M Keegan, M Abolghasemi - Australasian Joint Conference on Artificial …, 2023 - Springer
Abstract The Knapsack Problem is a classic problem in combinatorial optimisation. Solving
these problems may be computationally expensive. Recent years have seen a growing …

BUPNN: Manifold Learning Regularizer‐Based Blood Usage Prediction Neural Network for Blood Centers

L Pan, Z Zang, S Ma, W Hu, Z Hu - Computational Intelligence …, 2023 - Wiley Online Library
Blood centers are an essential component of the healthcare system, as timely blood
collection, processing, and efficient blood dispatch are critical to the treatment of patients …

Artificial Intelligence Related Healthcare Doctor Assistant and Consulting for Subscription-Based Applications

G Selvaraj, S Rajaprakash… - … on Computer Science …, 2023 - ieeexplore.ieee.org
Now we are in the period of Artificial Intelligence (AI), Machine Learning (ML) and
sophisticated technology. We are in a need of Artificial Intelligence related health care …

[PDF][PDF] Informatics in Medicine Unlocked

Automatic pancreas segmentation of CT scans enables physicians to identify and monitor
the abnormalities in the pancreas. This facilitates intraoperative assistance, surgical …