A Data-Driven Model Analysis Method in Optimizing Raw Materials Standard for Glutinous Rice Products

2021 ◽  
pp. 189-220
Author(s):  
Zhixin He ◽  
Zhou Kang ◽  
Jian Zhou ◽  
Hua Yang ◽  
Xuechun Shang ◽  
...  
Keyword(s):  
Raw Materials ◽  
Model Analysis ◽  
Data Driven ◽  
Analysis Method ◽  
Glutinous Rice

Reaction Heat of High Alkali Aluminosilicate Glass Batches in Melting Process

2014 ◽  
Vol 852 ◽  
pp. 71-75 ◽  
Author(s):  
Ying Liang Tian ◽  
Jin Shu Cheng ◽  
Jing Zhang ◽  
Yan Li Shao ◽  
Xiao Li
Keyword(s):  
Raw Materials ◽  
Melting Process ◽  
Aluminosilicate Glass ◽  
Heating Process ◽  
Analysis Method ◽  
Optimization Scheme ◽  
Reaction Heat ◽  
Significant Difference ◽  
Carbonate Decomposition ◽  
High Alkali

High alkali aluminosilicate glass batches were prepared by five different raw materials, reaction heat of which in melting process was studied by means of DSC thermal analysis method. The results show that reaction heat of batches in the heating process of 25-1600°C exists a significant difference, and which is among 4396.38 J/g-5311.14 J/g, moreover the least is the batches using petalite, while the most is spodumene. In the whole heating process, 380-800°C is carbonate decomposition stage, which accounts for 42-46% of the total absorbed heat; and 800-1200°C is silicate reaction stage, 40-50%; and 1200-1600°C is glass clarify and homogenization phase , 6%-16%. Therefore, carbonate decomposition and silicate reaction is the main part of batches heat consumption, the optimization scheme for materials has a significant effect on energy saving and emission reduction.

scholarly journals PENGENDALIAN PERSEDIAAN BAHAN BAKU DALAM PROSES PRODUKSI DENGAN MENGGUNAKAN METODE ECONOMIC ORDER QUANTITY (EOQ)

2019 ◽  
Vol 1 (2) ◽  
pp. 415-423
Author(s):  
Elia Rahayu R ◽  
Nor Norisanti ◽  
Acep Samsudin
Keyword(s):  
Raw Materials ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Analysis Method ◽  
Inventory Cost ◽  
Total Inventory ◽  
The Difference ◽  
Quantitative Descriptive

The purpose of this study is to control the supply of raw materials using the Economic Order Quantity (EOQ) method in Tahu Nugraha Jaya Sukabumi UKM. The data analysis method used is quantitative descriptive to describe and describe the data to be examined and then processed using EOQ. This study uses the EOQ method to determine the total inventory cost. The data needed in this study are the number of purchases of raw materials, the amount of use of raw materials, storage costs, and ordering costs. The results of this study indicate that by applying the EOQ method can further optimize the supply of raw materials by minimizing raw materials with increased inventory. With the application of the Economic Order Quantity (EOQ) method it shows more efficient than conventional methods of the company. Conclusions, seen from the difference in the TIC of the two methods, the more efficient method is the Economic Order Quantity (EOQ) method that is equal to 244,392.94 while the calculation used by the company is 374,325. so that it can be obtained that there is a difference between the Company TIC and the EIC method TIC. Keywords: Raw Material Inventory, Production Process

Development of cooked semi‑finished product of special purpose on the basis of gluten‑free raw materials

2021 ◽  
Vol 30 (3) ◽  
pp. 26-31
Author(s):  
L.T. Fahrtdinova ◽  
◽  
M.K. Sadigova ◽  
T.V. Kirillova ◽  
Yu. T. Saidullaeva ◽  
...  
Keyword(s):  
Rheological Properties ◽  
Corn Starch ◽  
Raw Materials ◽  
Rice Flour ◽  
Gluten Free ◽  
Analysis Method ◽  
Corn Flour ◽  
Composite Mixture ◽  
Control Version ◽  
Ratio Of Components

The article presents the results of a study on the development of a recipe for semi‑finished custard based on gluten‑free raw materials. The ratio of components in the gluten‑free mixture was optimized using the regression analysis method. The influence of gluten‑free raw materials on the rheological properties of the semi‑ finished product is studied. The variants of the experiment differed in the composition of the composite mixture (the ratio of corn, rice flour and corn starch). The chemical composition and the ratio of the components of the mixture determine the rheological properties of the semi‑finished product. The experimental version with the ratio of rice flour, corn flour and corn starch 50:40:10 most corresponds to the rheological properties of the control version and is characterized by high consumer properties.

scholarly journals Data-driven integration evaluation from the perspective of Adaboost and its application in WeChat public number ranking

2020 ◽  
Vol 309 ◽  
pp. 02017
Author(s):  
Yicheng Gong ◽  
Juan Zhao ◽  
Dongyang Zhang
Keyword(s):  
Factor Analysis ◽  
Adaptive Learning ◽  
Evaluation Model ◽  
Complex Structure ◽  
Principal Component ◽  
Data Driven ◽  
Analysis Method ◽  
Topsis Method ◽  
Evaluation Models ◽  
Weak Evaluation

The traditional comprehensive evaluation is difficult to model when dealing with large data with large parameters and complex structure, and it cannot adapt to the update of data. In order to improve this situation, this paper draws on the Adaptive Learning Adaboost perspective in statistical learning to develop a data-driven integrated evaluation model that updates the weight of sample weights and weak evaluation models with data. Three specific weak evaluation models were selected: data-driven Topsis method, principal component analysis method and factor analysis method. Taking the ranking of WeChat public account as an example, the results show that the accuracy of the integrated evaluation model is 88.57%, which is 17.14%, 31.43% and 28.57% higher than the data-driven Topsis method, principal component method and factor analysis method.

scholarly journals Bank Risk Determinants in Latin America

Risks ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 94
Author(s):  
Mariña Martínez-Malvar ◽  
Laura Baselga-Pascual
Keyword(s):  
Latin America ◽  
Commercial Banks ◽  
Banking Crises ◽  
Data Driven ◽  
Bank Risk ◽  
Z Score ◽  
Analysis Method ◽  
Gmm Estimator ◽  
Main Bank ◽  
Risk Determinants

Systemic Banking crises are a recurrent phenomenon that affects society, and there is a need for a better understanding of the risk factors to support prudential regulation and reduce unnecessary risk intake in the financial system. This paper examines the main bank risk determinants in Latin America. The period analysed covers the timespan from 1999 to 2013, including the systemic banking crisis episodes in Argentina (2001–2003) and Uruguay (2002–2005). We apply a new data-driven comparable methodology to classify and select commercial banks from the sample. We study bank risk proxied by the Z-score. We use the system-GMM estimator as our main empirical analysis method. According to our results, well capitalized, liquid, and traditional commercial banks are less risky. We perform robustness tests by applying OLS, and the results resemble our original model.

scholarly journals Multi-state data-driven gas path analysis method

2019 ◽  
Vol 158 ◽  
pp. 1565-1572 ◽  
Author(s):  
Shanxuan Tang ◽  
Hailong Tang ◽  
Min Chen
Keyword(s):  
Path Analysis ◽  
Data Driven ◽  
Analysis Method ◽  
State Data
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