Results 101 to 110 of about 164 (117)

Machine learning prediction of calorific value of coal based on the hybrid analysis

International Journal of Coal Preparation and Utilization, 2022
Zhiqiang Li, Yuemin Zhao, Zhaolin Lu, Wei Dai, Jinzhan Huang, Sen Cui, Biao Chen, Shenghong Wu, Liang Dong   +8 more
openaire   +1 more source

Prediction of Coal Calorific Value Based on a Hybrid Linear Regression and Support Vector Machine Model

2013
The gross calorific value (GCV) is an important property defining the efficiency of coal. There exist a number of correlations for estimating the GCV of a coal sample based upon its proximate and ultimate analyses. These correlations are mainly linear in character although there are indications that the relationship between the GCV and a few ...
Kelei Sun, Rongrong Gu, Huaping Zhou
openaire   +1 more source

Enhancing Real-Time Optimization with Machine Learning Predictions of Lower Calorific Values

This paper presents an enhancement to a Real-Time Optimization (RTO) strategy for industrial furnaces by integrating machine learning tech-niques. The developed methodology utilizes historical process data to build pre-dictive models that estimate the LCV, enabling more effective optimization of the fuel gas mixture, composed of different fuel gases ...
Filipe A. T. Silveira, Elcio H. Shiguemori   +1 more
openaire   +1 more source

Prediction of Calorific Value of Coal by Random Forest Regression Based on Limited Data

SSRN Electronic Journal, 2022
Kaan Büyükkanber, Hanzade Haykiri Acma, Serdar Yaman   +2 more
openaire   +1 more source

Machine learning prediction of calorific value of coal based on the hybrid analysis

International Journal of Coal Preparation and Utilization, 2023
Zhiqiang Li, Zhaolin Lu, Wei Dai
exaly  

Predicting calorific value of solid waste based on data augmentation and Auto-machine learning

The calorific value of solid waste is a vital parameter for the process design and techno-economic analysis of waste-to-energy thermal systems. However, existing predictive models are often constrained by limited dataset sizes and restricted geographical applicability.
Yuchao Guo, Xia Liu, Yuqing Zhang, Lei Liu, Weitong Pan, Xueli Chen, Longfei Tang, Guangsuo Yu, Yunfei Gao, Fuchen Wang   +9 more
openaire   +1 more source

Use of Fatty Acid Chemical Composition for Predicting Higher Calorific Value of Biodiesel

Materials Today: Proceedings, 2023
Sumod Pawar, Jitendra Hole, Mangesh Bankar, Subim Khan, Sagar Wankhade   +4 more
openaire   +1 more source

Calorific value prediction of coal and its optimization by machine learning based on limited samples in a wide range

Energy, 2023
Yaman S, Hanzade Haykiri-Acma
exaly  

Prediction of gross calorific value of solid fuels from their proximate analysis using soft computing and regression analysis

International Journal of Coal Preparation and Utilization, 2022
Moshood Onifade, Adeyemi Aladejare, Samson Bada   +2 more
exaly  

Analysis of Arithmetic Models for Predicting Calorific Values of Landfilled Municipal Solid Waste

2022
Diego Romeiro, Mariane Leme, Cíntia Takeda, Miriam Miguel   +3 more
openaire   +1 more source