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Found 6 papers, 0 papers with code
A general Framework for Utilizing Metaheuristic Optimization for Sustainable Unrelated Parallel Machine Scheduling: A concise overview
In this paper, we investigate the application of metaheuristic optimization algorithms to address the unrelated parallel machine scheduling problem (UPMSP) through the lens of sustainable development goals (SDGs).
A Comprehensive Study of Groundbreaking Machine Learning Research: Analyzing highly cited and impactful publications across six decades
As the field continues to evolve, it is crucial to understand the landscape of highly cited publications to identify key trends, influential authors, and significant contributions made thus far.
Breast Cancer Detection and Diagnosis: A comparative study of state-of-the-arts deep learning architectures
By improving the workflow of pathologists, these AI models have the potential to enhance the detection and diagnosis of breast cancer.
Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review
In this paper, a critical bibliometric analysis study is conducted, coupled with an extensive literature survey on recent developments and associated applications in machine learning research with a perspective on Africa.
Ebola Optimization Search Algorithm (EOSA): A new metaheuristic algorithm based on the propagation model of Ebola virus disease
To evaluate the proposed method's performance and capability compared with other optimization methods, the underlying propagation and mathematical models were first investigated to determine how they successfully simulate the EVD.
Metaheuristics optimized feedforward neural networks for efficient stock price prediction
This paper proposes the design and implementation of a hybrid symbiotic organisms search trained feedforward neural network model for effective and accurate stock price prediction.
