IEEE

Training Neural Operator Model and Solving Inverse Problems with AH FDTD Simulation Data

Abstract: This paper explores a data driven machine learning neural network, the neural operator network, as an alternative to traditional simulation methods for solving the inverse problem of the TMz ...
IEEE

Optimizing Problem-Solving in Technical Education: An Adaptive Learning System Based on Artificial Intelligence

Abstract: The increasing complexity of educational challenges in technical disciplines highlights the need for personalized learning systems to address diverse student needs. Traditional methods, ...
IEEE

Geo-Qwen: A Geometry Problem-Solving Method Based on Generative Large Language Models and Heuristic Reasoning

Abstract: Research on geometry problem solving is gaining increasing attention in the field of Natural Language Processing (NLP). Currently, research in geometry problem solving often relies on formal ...
IEEE

Fast Real-Time Neural Network-Based Kinematics Solving of the Cosserat Rod Model for a Parallel Continuum Surgical Manipulator

Abstract: The parallel continuum mechanism offers distinct advantages in the design of surgical manipulators, including enhanced stiffness, improved precision, and a simplified structure compared to ...
IEEE

A Neural Network Model Based on Differential Evolution Algorithm for Traveling Salesman Problem

Abstract: This paper presents a novel neural network-based optimization framework, NNDE, to solve the traveling salesman problem (TSP). The core idea is to use a radial basis function network (RBFN) ...
IEEE

The Development of the Flexible Periodic Vehicle Routing Problem Model for Gas Cylinders Distribution

Abstract: Distribution plays a crucial role in business processes, and an efficient distribution system is necessary to minimize costs. Many companies, including those in the gas industry, are ...
IEEE

Large Language Model Implemented Simulated Annealing Algorithm for Traveling Salesman Problem

Abstract: Large language models (LLMs) have recently attracted significant attention and permeated diverse fields and disciplines. This paper aims to investigate the efficacy of LLMs in efficiently ...
IEEE

Constraint Programming Based Model and Algorithm for Solving Steelmaking and Continuous Casting Scheduling Problem with Adjustable Casting Time

Abstract: The Steelmaking-Continuous Casting (SCC) scheduling problem is usually regarded as a type of hybrid flow-shop scheduling problems (HFSP) with special process constraints. To research the SCC ...
The Atlantic

The Problem With Letting AI Do the Grunt Work

One of the first sentences I was ever paid to write was “Try out lighter lip stick colors, like peach or coral.” Fresh out of college in the mid 2010s, I’d scored a copy job for a how-to website. An ...
IEEE

Genetic Algorithm Based Digital Workshop Scheduling Model Solving

Abstract: In order to improve the productivity of the workshop and reduce the manufacturing cost, this paper carries out an in-depth analysis and research on the complex workshop environment based on ...
IEEE

PUP-Net: A Twofold Physical Model Embedded 3-D U-Net With Polarization Fusion for Solving Inverse Scattering Problems With a Sparse Planar Array

Abstract: In this article, a twofold physical model (PM) embedded 3-D U-Net with polarization fusion (PF), referred to as PUP-Net, is proposed for solving 3-D inverse scattering problems (ISPs) with a ...
Frontiers

Arduino-based fine particulate matter STEM program: enhancing problem-solving and collaboration in a post-pandemic blended high school setting

The outbreak of COVID-19 has triggered a significant transformation in the educational landscape, particularly with the widespread adoption of blended learning, which combines face-to-face and remote ...