Prediction of higher heating value of biomass materials based on proximate analysis using gradient boosted regression trees method-Reference-Cited by-同舟云学术

Prediction of higher heating value of biomass materials based on proximate analysis using gradient boosted regression trees method

Published:2019-07-11 Issue:6 Volume:43 Page:672-681
ISSN:1556-7036
Container-title:Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
language:en
Short-container-title:Energy Sources, Part A: Recovery, Utilization, and Environmental Effects

Author:

Samadi Seyed Hashem¹,Ghobadian Barat¹,Nosrati Mohsen²

Affiliation:

1. Department of Biosystems Engineering, Tarbiat Modares University, Tehran, Iran

2. Biotechnology Group, Chemical Engineering Department, Tarbiat Modares University, Tehran, Iran

Publisher

Informa UK Limited

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://www.tandfonline.com/doi/pdf/10.1080/15567036.2019.1630521

Reference40 articles.

1. Predicting Coal Heating Values Using Proximate Analysis via a Neural Network Approach

2. ANFIS based prediction model for biomass heating value using proximate analysis components

3. BP. 2017. BP statistical review of world energy 2017. British Petroleum 1–52. Accessed. http://www.bp.com/content/dam/bp/en/corporate/pdf/energy-economics/statistical-review-2017/bp-statistical-review-of-world-energy-2017-full-report.pdf

4. Prediction models for higher heating value based on the structural analysis of the biomass of plant remains from the greenhouses of Almería (Spain)

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