Abstract: Dynamic quadratic programming (DQP) widely exists in many optimization applications. Existing recurrent neural networks (RNNs) exhibit significant limitations in solving DQP, including ...
Subquadratic, a company developing a novel generative artificial intelligence model, launched today with $29 million in seed funding. The new large language model, dubbed SubQ, uses what the company ...
Abstract: Various discrete-time zeroing neural network (DTZNN) models have been developed for solving dynamic constrained quadratic programming. However, two challenges persist within the DTZNN ...
ABSTRACT: Grover’s algorithm is widely celebrated as providing quadratic quantum speedup for unsorted database search, forming the theoretical foundation for numerous claimed quantum advantages in ...
wget https://github.com/yangao07/abPOA/releases/download/v1.5.6/abPOA-v1.5.6.tar.gz tar -zxvf abPOA-v1.5.6.tar.gz && cd abPOA-v1.5.6 abPOA is an extended version of ...
Large-scale distributed renewable energy in the distribution network can result in reliability issues such as exceeding voltage limits and overloading power lines. Additionally, the rapid growth of ...
The reformations of the electrical power sector have resulted in very dynamic and competitive market that has changed many elements of the power industry. Excessive demand of energy, depleting the ...
We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. We ...
This paper presents a continuous method for solving binary quadratic programming problems. First, the original problem is converted into an equivalent continuous optimization problem by using NCP ...
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