Search Results for author:
Found 15 papers, 1 papers with code
A Hybrid Intelligent Framework for Maximising SAG Mill Throughput: An Integration of Expert Knowledge, Machine Learning and Evolutionary Algorithms for Parameter Optimisation
This study introduces a hybrid intelligent framework leveraging expert knowledge, machine learning techniques, and evolutionary algorithms to address this research need.
Hybrid Inception Architecture with Residual Connection: Fine-tuned Inception-ResNet Deep Learning Model for Lung Inflammation Diagnosis from Chest Radiographs
Diagnosing lung inflammation, particularly pneumonia, is of paramount importance for effectively treating and managing the disease.
A Novel Hybrid Algorithm for Optimized Solutions in Ocean Renewable Energy Industry: Enhancing Power Take-Off Parameters and Site Selection Procedure of Wave Energy Converters
This study delves into the optimization of power take-off (PTO) parameters and the site selection process for an offshore oscillating surge wave energy converter (OSWEC).
Brain Tumor Detection and Classification Using a New Evolutionary Convolutional Neural Network
A definitive diagnosis of a brain tumour is essential for enhancing treatment success and patient survival.
Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter
Ocean wave renewable energy is fast becoming a key part of renewable energy industries over the recent decades.
GTOPX Space Mission Benchmarks
This contribution introduces the GTOPX space mission benchmark collection, which is an extension of GTOP database published by the European Space Agency (ESA).
Hybrid Neuro-Evolutionary Method for Predicting Wind Turbine Power Output
Reliable wind turbine power prediction is imperative to the planning, scheduling and control of wind energy farms for stable power production.
Optimisation of Large Wave Farms using a Multi-strategy Evolutionary Framework
The primary goal of this research is to maximise the total harnessed power of a large wave farm consisting of fully-submerged three-tether wave energy converters (WECs).
An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study of the Lillgrund Offshore Wind Farm
Accurate short-term wind speed forecasting is essential for large-scale integration of wind power generation.
Design optimisation of a multi-mode wave energy converter
A wave energy converter (WEC) similar to the CETO system developed by Carnegie Clean Energy is considered for design optimisation.
A Hybrid Cooperative Co-evolution Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters
Such arrays can be optimised for total energy output by adjusting both the relative positions of buoys in farms and also the power-take-off (PTO) parameters for each buoy.
Covariance Matrix Adaptation Greedy Search Applied to Water Distribution System Optimization
This is followed by an upward-greedy search phase to remove pressure violations.
Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation
The installed amount of renewable energy has expanded massively in recent years.
A new insight into the Position Optimization of Wave Energy Converters by a Hybrid Local Search
We compare the proposed hybrid method with other state-of-the-art search methods in five different wave scenarios -- one simplified irregular wave model and four real wave climates.
A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters
In this research, we investigate the problem of maximising the energy delivered by farms of wave energy converters (WEC's).
