
Machine learning algorithms
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This article conducts an exhaustive investigation into the utilization of machine learning (ML) methods for forecasting the maximum load capacity (MLC) of circular reinforced concrete columns (CRCC) using Fiber-Reinforced Polymer (FRP). Extreme Gradient Boosting (XGB) algorithm is combined with novel metaheuristic algorithms, namely Sailfish Optimizer and Aquila Optimizer, to fine-tune its hyperparameters.
18p
viengfa
28-10-2024
2
2
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Predicting the macroscopic permeability of porous media is critical in various scientific and engineering applications. This study proposes a novel model that combines Random Forest (RF) and rime-ice (RIME) optimization algorithm, denoted RIME-RF-RIME, to predict permeability based on six key features covering fluid phase dimensions, geometric characteristics, surrounding phase permeability, and media porosity.
14p
viengfa
28-10-2024
2
2
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Efficient ship detection is essential for inland waterway management. Recent advances in artificial intelligence have prompted research in this field. This study introduces a real-time ship detection model utilizing computer vision and the YOLO object detection framework.
14p
viengfa
28-10-2024
2
2
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This paper presents the development of an Artificial Intelligence (AI) and Machine Learning (ML) model designed to detect cracks on concrete surfaces. The objective is to enhance the automation, precision, and performance of crack detection using the computer vision algorithm.
13p
viengfa
28-10-2024
2
2
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This paper is aimed to apply hybrid machine learning model namely GA-ANFIS, which is a combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Genetic Algorithm (GA), for the prediction of total bearing capability of driven piles.
8p
viengfa
28-10-2024
3
2
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Adaptive Neuro-Based Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) algorithms were utilized to produce numerical tools for predicting the bond strength between the concrete surface and carbon fiber reinforced polymer (CFRP) sheets.
11p
viengfa
28-10-2024
2
2
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The chosen algorithm for this project is the MLP (Multi-layer Perceptron) classifier, which has seen significant development in recent years and has widespread applications in various Al domains. This is why it has been selected as the foundation for the system in this project. The research topic aims to utilize this algorithm to construct a system that rapidly predicts whether a mushroom is edible or poisonous, facilitating practical applications.
13p
viuzumaki
28-03-2025
4
0
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Bài giảng "Máy học nâng cao: Artificial neural netword" cung cấp cho người đọc các nội dung: Introduction, perceptron, neural network, backpropagation algorithm. Mời các bạn cùng tham khảo nội dung chi tiết.
62p
myhouse06
24-03-2025
3
1
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Bài giảng "Máy học nâng cao: Genetic algorithm" cung cấp cho người đọc các nội dung: Introduction - Genetic algorithm (GA), Genetic algorithm operators and parameters, example, homework. Mời các bạn cùng tham khảo nội dung chi tiết.
70p
myhouse06
24-03-2025
0
0
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Recently, machine learning (ML) algorithms have proven to be highly effective tools for predicting structural damage. However, the data used in structural health monitoring often consists primarily of normal operational conditions or slight deviations from the original state, with a scarcity of data representing potentially dangerous conditions.
21p
viyamanaka
06-02-2025
1
1
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Currently, the field of science and technology, particularly Artificial Intelligence (AI), is undergoing significant progress. AI involves the computer-based simulation of human cognitive functions. Within the realm of AI, machine learning, a specialized branch, utilizes mathematical algorithms to enhance computational capabilities.
10p
viyamanaka
06-02-2025
3
2
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Short-term prediction of regional energy consumption by metaheuristic optimized deep learning models
Modern civilization is heavily dependent on energy, which burdens the energy sector. Therefore, a highly accurate energy consumption forecast is essential to provide valuable information for efficient energy distribution and storage. This study proposed a hybrid deep learning model, called I-CNN-JS, by incorporating a jellyfish search (JS) algorithm into an ImageNetwinning convolutional neural network (I-CNN) to predict weekahead energy consumption.
6p
vibenya
31-12-2024
6
2
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This review explores recent ML advancements in assessing corrosion in RC structures. Various algorithms, such as Artificial Neural Networks (ANNs), Gene Expression Programming (GEP), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM) and Ensemble Learning, have shown potential in estimating corrosion processes, predicting material properties, and evaluating structural durability.
7p
vibenya
31-12-2024
6
2
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Bài 2 trình bày về Concept Learning. Các nội dung chính trong bài này gồm có: Learning from examples, general-to specific ordering of hypotheses, version spaces and candidate elimination algorithm. Mời các bạn cùng tham khảo.
25p
youcanletgo_04
17-01-2016
94
16
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In this paper, we propose a mechanism to optimize range of EV by integrating some of the best methods to estimate rotor position, efficient temperature control modules and machine learning algorithms that analyze the vehicle’s environment and driving pattern.
10p
lucastanguyen
01-06-2020
23
2
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The purpose of this paper is to examine the extent to which the Intelligent Enterprise Resource Planning (I-ERP) System can be used in company operations. Machine learning is embedded in a decision tree algorithm to demonstrate the viability of intelligent technology in an ERP system and to enhance the quality of operations through an I-ERP system.
12p
tohitohi
22-05-2020
36
2
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In this research, we put the development of a no-wait flow-shop scheduling model alongside with the effect of learning into consideration to minimize the cost of consumption of resources.
20p
tohitohi
22-05-2020
43
1
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Web search engine: Markov chain theory Data Mining, Machine Learning: Data mining, Machine learning: Stochastic gradient, Markov chain Monte Carlo, Image processing: Markov random fields, Design of wireless communication systems: random matrix theory, Optimization of engineering processes: simulated annealing, genetic algorithms, Finance (option pricing, volatility models): Monte Carlo, dynamic models, Design of atomic bomb (Los Alamos): Markov chain Monte Carlo.
16p
quangchien2205
30-03-2011
89
7
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