Extreme learning machine

Accurate forecasting of the electrical load is a critical element for grid operators to make well-informed decisions concerning electricity generation, transmission, and distribution. In this study, an Extreme Learning Machine (ELM) model was proposed and compared with four other machine learning models including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU).

10p viengfa 28-10-2024 2 1   Download

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   Download

The Axial Load Capacity (ALC) of Concrete-Filled Steel Tubular (CFST) structural members is regarded as one of the most crucial technical factors for the design of these composite structures.

17p viengfa 28-10-2024 2 2   Download

In this study, four machine learning models have been studied which are Artificial Neural Networks, Convolutional Neural Networks, Long Short-Term Memory (LSTM) and Extreme Learning Machine (ELM). They have been used to forecast the solar power of Nhi Ha solar farm in short-term.

8p viyoko 01-10-2024 3 1   Download

The primary objective of this research is to develop an ML-PTF on the extreme gradient boosting (XGB) framework capable of estimating soil compression index with high precision and low effort. Furthermore, advancing the quantitative knowledge of which soil structural indicators determine soil compressibility using correlation analysis.

12p vifaye 20-09-2024 3 1   Download

Nghiên cứu này đề xuất một phương pháp phân loại ảnh viễn thám siêu phổ (AVTSP). Chúng tôi sử dụng một khung mạng nơ-ron tích chập mới để trích xuất các đặc điểm cục bộ của ảnh viễn thám siêu phổ, và sau đó sử dụng một thuật toán máy học hạt nhân cấp tốc (kernel extreme learning machine, KELM) để phân loại các đối tượng khác nhau.

4p visergeybrin 25-11-2021 29 4   Download

Pricing and guessing the right prices are vital for both hosts and renters on homesharing plat-form from internet based companies. To contribute the growing interest and immense literatureon applying Artificial Intelligence on predicting rental prices, this paper attempts to build ma-chine learning models for that purpose using the Luxstay listings in Hanoi. R2 score is used as the main criterion for the model performance and the results show that Extreme GradientBoostings (XGB) is the model with the best performance with R2= 0.

44p hoanghung9393 28-08-2020 12 3   Download

Trong bài báo này các tác giả trình bài một cách tiếp cận mới để đo HCT từ cung dòng điện được tạo ra bởi phản ứng hóa học trong quá trình đo glucose của các thiết bị cầm tay. Phương pháp đề xuất dựa trên mạng neural nhân tạo được huấn luyện online dựa trên máy học cực độ (Extreme Learning Machine - ELM). Những kết quả thực nghiệm cho thấy, phương pháp đề nghị cho kết quả khả quan khi so sánh với các phương pháp trước.

8p binhminhmuatrenngondoithonggio 09-06-2017 75 3   Download

This paper proposes a procedural pipeline for wind forecasting based on clustering and regression. First, the data are clustered into groups sharing similar dynamic properties. Then, data in the same cluster are used to train the neural network that predicts wind speed. For clustering, a hidden Markov model (HMM) and the modified Bayesian information criteria (BIC) are incorporated in a new method of clustering time series data.

16p dieutringuyen 07-06-2017 37 2   Download