ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...
Abstract: In this paper, a modified hybrid conjugate gradient method is proposed for solving unconstrained optimization problems and a new sufficient descent direction is proposed. The theoretical ...
This study introduced an efficient method for solving non-linear equations. Our approach enhances the traditional spectral conjugate gradient parameter, resulting in significant improvements in the ...
Abstract: Different optimization approaches are explored to solve unconstrained minimization problems numerically in this paper. A classic optimization problem i.e., the Rosenbrock function is ...
Department of Mechanical Engineering, University of Cape Town, Cape Town, South Africa This paper presents the exergy analysis and optimization of the Stirling engine, which has enormous potential for ...
A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...
The factoring of biprimes is proposed as a framework for exploring unconstrained optimization algorithms. A mapping from a given factoring problem to a positive degree four polynomial F is described.
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