scholarly journals DECISION TREE APPROACH FOR PLANTS STOPPAGE DECISION PROCESS DUE TO POWER LIMITATION CASE STUDY: STEEL COMPANY

2021 ◽  
Author(s):  
Mohamed Saied Essa Othman Hussein
Keyword(s):  
Decision Tree ◽  
Decision Process ◽  
Steel Company ◽  
Tree Approach

scholarly journals Energy Scheduling Using Decision Trees and Emulation: Agriculture Irrigation with Run-of-the-River Hydroelectricity and a PV Case Study

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3987 ◽  
Author(s):  
Omid Abrishambaf ◽  
Pedro Faria ◽  
Zita Vale ◽  
Juan M. Corchado
Keyword(s):  
Decision Tree ◽  
High Energy ◽  
Efficient Solutions ◽  
World Population ◽  
Technical Validation ◽  
Agriculture Irrigation ◽  
Technical Features ◽  
High Energy Consumption ◽  
Tree Approach

Agriculture is the very backbone of every country. Unfortunately, agricultural sustainability is threatened by the lack of energy-efficient solutions. The threat becomes more evident with the constantly growing world population. The research community must, therefore, focus on resolving the problem of high energy consumption. This paper proposes a model of energy scheduling in agricultural contexts. Greater energy efficiency is achieved by means of PV (photovoltaics) and hydropower, as demonstrated in the conducted case study. The developed model is intended for contexts where the farm is located near a river, so the farmer can use the flowing water to produce energy. Moreover, the model has been emulated using a variety of state-of-the-art laboratory devices. Optimal energy scheduling is performed via a decision tree approach, optimizing the use of energy resources and reducing electricity costs. Finally, a realistic scenario is presented to show the technical features and the practical behaviors of each emulator when adapting the results of the decision tree. The research outcomes demonstrate the importance of the technical validation of each model. In addition, the results of the emulation reveal practical issues that had not been discovered during the theoretical study or during the simulation.

Evaluating the Economic Efficiency of Wildfire Rehabilitation Treatments

1987 ◽  
Vol 2 (2) ◽  
pp. 58-61
Author(s):  
Jay Sullivan ◽  
Philip N. Omi ◽  
A. Allen Dyer ◽  
Armando Gonzáles-Cabán
Keyword(s):  
Decision Tree ◽  
Pacific Northwest ◽  
Economic Efficiency ◽  
Rocky Mountains ◽  
Decision Process ◽  
Forest Service ◽  
Usda Forest Service ◽  
Northern Rocky Mountains ◽  
The Pacific ◽  
Tree Approach

Abstract The success of emergency wildfire rehabilitation treatments applied on USDA Forest Service land is rarely documented. Though based partially on economic efficiency criteria, treatments are often applied with little consideration of the risks involved. A decision-tree approach incorporates such risks in the rehabilitation decision process through the calculation of an expected value. This approach was applied to documented rehabilitation projects conducted on Forest Service land in the Pacific Northwest and northern Rocky Mountains from 1976 to 1981. The evaluation of past projects showed that a number of inefficient projects have been applied even without considering risk. When the risks of applying treatments are included, the efficiency of nearly all of the rehabilitation efforts becomes suspect. West. J. Appl. For. 2(2):58-61, April, 1987.

Penerapan Metode Klasifikasi Decision Tree dan Algoritma C4.5 dalam Memprediksi Kriteria Nasabah Kredit Mega Auto Finance

2020 ◽  
Vol 7 (2) ◽  
pp. 200
Author(s):  
Puji Santoso ◽  
Rudy Setiawan
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Microsoft Excel ◽  
Customer Data ◽  
Data Mining Techniques ◽  
C4.5 Algorithm ◽  
Marketing Costs ◽  
Excel Format ◽  
Data Mining Application

One of the tasks in the field of marketing finance is to analyze customer data to find out which customers have the potential to do credit again. The method used to analyze customer data is by classifying all customers who have completed their credit installments into marketing targets, so this method causes high operational marketing costs. Therefore this research was conducted to help solve the above problems by designing a data mining application that serves to predict the criteria of credit customers with the potential to lend (credit) to Mega Auto Finance. The Mega Auto finance Fund Section located in Kotim Regency is a place chosen by researchers as a case study, assuming the Mega Auto finance Fund Section has experienced the same problems as described above. Data mining techniques that are applied to the application built is a classification while the classification method used is the Decision Tree (decision tree). While the algorithm used as a decision tree forming algorithm is the C4.5 Algorithm. The data processed in this study is the installment data of Mega Auto finance loan customers in July 2018 in Microsoft Excel format. The results of this study are an application that can facilitate the Mega Auto finance Funds Section in obtaining credit marketing targets in the future

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