SciELO

Precision crack analysis in concrete structures using CNN, SVM, and KNN: a machine learning approach

Cracks in structures are discontinuities that occur due to stress, material degradation, or design flaws, compromising structural integrity. Detecting and analyzing cracks is crucial for assessing ...

Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to cleaning ingredients (handling missing values, standardization) Model ...
IEEE

Non-Intrusive Load Monitoring Modeling and Analysis Based on Optimized K-Nearest Neighbor Algorithm

Abstract: Aiming at the problem that the recognition rate of the K-Nearest Neighbor (KNN) algorithm is not high in the face of similar power fingerprints in non-intrusive load recognition, an improved ...
GitHub

meta-heuristic-algorithms

This project aimed to implement three well-known meta-heuristic algorithms: cuckoo search (CS), bat algorithm (BA), and flower pollination algorithm (FPA). We found that three algorithms could have a ...
IEEE

Diagnosis of Demagnetization Faults in PMSGs Based on Performance Evaluation of Machine Learning Algorithms Through Flux and Current Signals

Abstract: This study proposed an effective machine learning (ML)-based fault diagnosis method for demagnetization faults, including “healthy, 30% unipolar demagnetization, 50% multimagnet ...
GitHub

Python Maze Solver using A* Algorithm with Movement Constraints

A Python script with an AI algorithm that solves a 2D maze using the A* search algorithm - but, with specific movement constraints, to really force the AI earn its way out of the maze. This time, ...