XGBoost‐based intelligence yield prediction and reaction factors analysis of amination reaction

2021 ◽  
Author(s):  
Jing Dong ◽  
Lichao Peng ◽  
Xiaohui Yang ◽  
Zelin Zhang ◽  
Puyu Zhang
Keyword(s):  
Yield Prediction ◽  
Factors Analysis ◽  
Amination Reaction

scholarly journals Intelligent predicting reaction performance in multi-dimensional chemical space using quantile regression forest

2021 ◽  
Vol 87 (2) ◽  
pp. 299-318
Author(s):  
◽  
Jing Dong ◽  
Xuechun Mu ◽  
Zelin Zhang ◽  
Yuqing Zhang ◽  
...  
Keyword(s):  
Organic Chemistry ◽  
Machine Learning ◽  
Chemical Space ◽  
Yield Prediction ◽  
Feature Descriptors ◽  
Amination Reaction ◽  
Prediction Technique ◽  
Experimental Process ◽  
Reaction Performance ◽  
Feature Dimensionality Reduction

Buchwald-Hartwig amination reaction is widely applied in synthetic organic chemistry, which faces tedious and complex experimental process. In 2018, an interesting yield prediction technique is proposed via machine learning (random forest) in Science. However, the method is based on point prediction with many feature descriptors. For tackling these problems, complements and improvements have been made from the perspectives of machine learning and statistics, including feature dimensionality reduction, distributed prediction and visualization, so as to provide accurate and reliable decision information.

An Application of the HFACS Method to Aviation Accidents in Africa

2016 ◽  
Vol 6 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Isaac Munene
Keyword(s):  
Human Factors ◽  
Physical Environment ◽  
Human Factor ◽  
Flight Training ◽  
African Countries ◽  
Causal Factors ◽  
Aviation Accidents ◽  
Factors Analysis ◽  
Adverse Weather ◽  
Decision Errors

Abstract. The Human Factors Analysis and Classification System (HFACS) methodology was applied to accident reports from three African countries: Kenya, Nigeria, and South Africa. In all, 55 of 72 finalized reports for accidents occurring between 2000 and 2014 were analyzed. In most of the accidents, one or more human factors contributed to the accident. Skill-based errors (56.4%), the physical environment (36.4%), and violations (20%) were the most common causal factors in the accidents. Decision errors comprised 18.2%, while perceptual errors and crew resource management accounted for 10.9%. The results were consistent with previous industry observations: Over 70% of aviation accidents have human factor causes. Adverse weather was seen to be a common secondary casual factor. Changes in flight training and risk management methods may alleviate the high number of accidents in Africa.

Postoperative Complications in Pituitary Adenomas: A Retrospective Risk Factors Analysis

2019 ◽  
Author(s):  
Giuliana Frasson ◽  
Diego Cazzador ◽  
Filippo Perozzo ◽  
Giuseppe Rolma ◽  
Sara Munari ◽  
...  
Keyword(s):  
Risk Factors ◽  
Postoperative Complications ◽  
Pituitary Adenomas ◽  
Factors Analysis

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

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