scholarly journals Prediction of CO2 Solubility in Ionic Liquids Based on Multi-Model Fusion Method

Processes ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 258 ◽  
Author(s):  
Luyue Xia ◽  
Jiachen Wang ◽  
Shanshan Liu ◽  
Zhuo Li ◽  
Haitian Pan
Keyword(s):  
Ionic Liquids ◽  
Information Entropy ◽  
Research Work ◽  
Entropy Method ◽  
Modeling Method ◽  
Least Square ◽  
Fusion Model ◽  
Co2 Solubility ◽  
Model Fusion ◽  
Better Than

Reducing the emissions of greenhouse gas is a worldwide problem that needs to be solved urgently for sustainable development in the future. The solubility of CO2 in ionic liquids is one of the important basic data for capturing CO2. Considering the disadvantages of experimental measurements, e.g., time-consuming and expensive, the complex parameters of mechanism modeling and the poor stability of single data-driven modeling, a multi-model fusion modeling method is proposed in order to predict the solubility of CO2 in ionic liquids. The multiple sub-models are built by the training set. The sub-models with better performance are selected through the validation set. Then, linear fusion models are established by minimizing the sum of squares of the error and information entropy method respectively. Finally, the performance of the fusion model is verified by the test set. The results showed that the prediction effect of the linear fusion models is better than that of the other three optimal sub-models. The prediction effect of the linear fusion model based on information entropy method is better than that of the least square error method. Through the research work, an effective and feasible modeling method is provided for accurately predicting the solubility of CO2 in ionic liquids. It can provide important basic conditions for evaluating and screening higher selective ionic liquids.

scholarly journals Prediction of the Solubility of CO2 in Imidazolium Ionic Liquids Based on Selective Ensemble Modeling Method

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1369
Author(s):  
Luyue Xia ◽  
Shanshan Liu ◽  
Haitian Pan
Keyword(s):  
Ionic Liquids ◽  
Co2 Capture ◽  
Entropy Method ◽  
Modeling Method ◽  
Ensemble Model ◽  
Ensemble Modeling ◽  
Co2 Solubility ◽  
Fully Integrated ◽  
Imidazolium Ionic Liquids ◽  
Selective Ensemble

Solubility data is one of the essential basic data for CO2 capture by ionic liquids. A selective ensemble modeling method, proposed to overcome the shortcomings of current methods, was developed and applied to the prediction of the solubility of CO2 in imidazolium ionic liquids. Firstly, multiple different sub–models were established based on the diversities of data, structural, and parameter design philosophy. Secondly, the fuzzy C–means algorithm was used to cluster the sub–models, and the collinearity detection method was adopted to eliminate the sub–models with high collinearity. Finally, the information entropy method integrated the sub–models into the selective ensemble model. The validation of the CO2 solubility predictions against experimental data showed that the proposed ensemble model had better performance than its previous alternative, because more effective information was extracted from different angles, and the diversity and accuracy among the sub–models were fully integrated. This work not only provided an effective modeling method for the prediction of the solubility of CO2 in ionic liquids, but also provided an effective method for the discrimination of ionic liquids for CO2 capture.

Optimal Hedge Ratio and Hedging Effectiveness in Stock Futures Market: Evidence from National Stock Exchange, India

2019 ◽  
Vol 118 (3) ◽  
pp. 137-152
Author(s):  
A. Shanthi ◽  
R. Thamilselvan
Keyword(s):  
Banking Sector ◽  
Stock Exchange ◽  
Research Work ◽  
Futures Market ◽  
Least Square ◽  
Time Varying ◽  
Hedge Ratio ◽  
Hedging Effectiveness ◽  
Out Of Sample ◽  
Optimal Hedge

The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets

scholarly journals Application of Blockchain for Supply Chain Financing: Explaining the Drivers Using SEM

2021 ◽  
Vol 7 (3) ◽  
pp. 167
Author(s):  
Mohammad Rokibul Kabir ◽  
Md. Aminul Islam ◽  
Marniati ◽  
Herawati
Keyword(s):  
Supply Chain ◽  
Technology Acceptance ◽  
Structural Equation ◽  
Research Work ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Innovation Research ◽  
Supply Chain Financing ◽  
The Impact

Owing to the lack of research in emerging Asian nations, this research aimed to unearth the determinants of blockchain acceptance for supply chain financing by a Bangladeshi financing company called IPDC. Centred on a technology acceptance framework called UTAUT (unified theory of acceptance and use of technology) and open innovation research, an expanded model with a mediating variable is developed for this study. This research work employs the deductive inference method in conjunction with the positivism paradigm. A structural questionnaire was used to gather data, which were then processed through Smart-PLS (partial least square) for SEM (structural equation modeling). The survey includes all the people who are directly or indirectly involved in the supply chain financing platform of IPDC. The study consists of seven direct hypotheses and one mediating hypothesis. The results show that all the direct hypotheses except the impact of social influence on the behavioural intention to use (BINTU) blockchain are significant. The mediating hypothesis indicating the role of BINTU in the relationship between facilitating conditions (FCON) and the actual use of blockchain is also supported. FCON and BINTU together explain 88.7% variation in blockchain use behaviour for supply chain financing. The research advances past findings by employing an expanded UTAUT framework and validating observations with the other relevant studies throughout the world.

Eutectic ionic liquid mixtures and their effect on CO2 solubility and conductivity

RSC Advances ◽  
2015 ◽  
Vol 5 (63) ◽  
pp. 51407-51412 ◽  
Author(s):  
Anna S. Ivanova ◽  
Thomas Brinzer ◽  
Elliot A. Roth ◽  
Victor A. Kusuma ◽  
John D. Watkins ◽  
...  
Keyword(s):  
Ionic Liquid ◽  
Ionic Liquids ◽  
Binary System ◽  
Liquid Mixtures ◽  
Short Chain ◽  
Co2 Solubility

A simple binary system of compounds resembling short-chain versions of popular ionic liquids has been shown to have alloying properties.

Civil Aeroengine Fault Diagnosis Based on Fuzzy Least Square Support Vector Machine

2011 ◽  
Vol 130-134 ◽  
pp. 2047-2050 ◽  
Author(s):  
Hong Chun Qu ◽  
Xie Bin Ding
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Coefficient Matrix ◽  
Least Square ◽  
Support Vector ◽  
Influence Coefficient ◽  
Structural Risk ◽  
Better Than

SVM(Support Vector Machine) is a new artificial intelligence methodolgy, basing on structural risk mininization principle, which has better generalization than the traditional machine learning and SVM shows powerfulability in learning with limited samples. To solve the problem of lack of engine fault samples, FLS-SVM theory, an improved SVM, which is a method is applied. 10 common engine faults are trained and recognized in the paper.The simulated datas are generated from PW4000-94 engine influence coefficient matrix at cruise, and the results show that the diagnostic accuracy of FLS-SVM is better than LS-SVM.

scholarly journals Intelligent Prediction of Sieving Efficiency in Vibrating Screens

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Bin Zhang ◽  
Jinke Gong ◽  
Wenhua Yuan ◽  
Jun Fu ◽  
Yi Huang
Keyword(s):  
Support Vector Machine ◽  
Cross Validation ◽  
Prediction Performance ◽  
Least Square ◽  
Support Vector ◽  
Adaptive Genetic Algorithm ◽  
Screen Length ◽  
Vibrating Screen ◽  
Working Parameters ◽  
Better Than

In order to effectively predict the sieving efficiency of a vibrating screen, experiments to investigate the sieving efficiency were carried out. Relation between sieving efficiency and other working parameters in a vibrating screen such as mesh aperture size, screen length, inclination angle, vibration amplitude, and vibration frequency was analyzed. Based on the experiments, least square support vector machine (LS-SVM) was established to predict the sieving efficiency, and adaptive genetic algorithm and cross-validation algorithm were used to optimize the parameters in LS-SVM. By the examination of testing points, the prediction performance of least square support vector machine is better than that of the existing formula and neural network, and its average relative error is only 4.2%.

Application of Fuzzy Comprehensive Evaluation Based on Entropy Method in the General Layout and Transportation Design Optimization

2011 ◽  
Vol 94-96 ◽  
pp. 210-213
Author(s):  
Qiu Ping Wang ◽  
Yan Hua Yu
Keyword(s):  
Program Evaluation ◽  
Information Entropy ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Entropy Method ◽  
Evaluation Index ◽  
Fuzzy Mathematics ◽  
Objective Method ◽  
Fuzzy Weight

Based on the design of general layout and transportation optimization of a variety of factors, established a program evaluation system, the theory of fuzzy mathematics general layout and transportation design a comprehensive evaluation. For the fuzzy weight of each factor to determine the application of an objective method of empowerment from the perspective of information entropy to determine the factors enabling the weight of each evaluation index, fuzzy comprehensive evaluation of the results obtained. To detail with an example.

scholarly journals Agriculture, Manufacturing and Economic Growth in Nigeria

2021 ◽  
Vol 04 (03) ◽  
Author(s):  
Atayi Abraham Vincent ◽  
Keyword(s):  
Government Spending ◽  
Agricultural Sector ◽  
Manufacturing Sector ◽  
Research Work ◽  
Least Square Method ◽  
Least Square ◽  
Ordinary Least Square ◽  
Positive Effects ◽  
The Government ◽  
Positive Effect

This research work address the positive effect of Agriculture on the manufacturing sector in Nigeria. The study made used of Ordinary Least Square Method estimation techniques. The findings showed that Agricultural output, government spending on agriculture, and real gross domestic product all have positive effects on the manufacturing sector. The effects is RGDP 66percent, AGRQ by 63%, and GOEXA by 96 percent. The study recommends among other things that government should allocate more resources to the Nigerian agricultural sector and ensure that the funds are judiciously use and that the government should also seek to strengthen its incentives for the manufacturing sector in order to promote increased industrial production and growth.

scholarly journals People counter on CCTV video using histogram of oriented gradient and Kalman filter methods

2020 ◽  
Vol 8 (3) ◽  
pp. 222-227
Author(s):  
Faisal Dharma Adhinata ◽  
Muhammad Ikhsan ◽  
Wahyono Wahyono
Keyword(s):  
Kalman Filter ◽  
Mutual Information ◽  
Public Service ◽  
Information Entropy ◽  
Support Service ◽  
Entropy Method ◽  
Histogram Of Oriented Gradient ◽  
Filter Methods ◽  
Human Object ◽  
Long Time

CCTV cameras have an important function in the field of public service, especially for convenience. The objects recorded through CCTV cameras are processed into information to support service satisfaction in the community. This study uses the function of CCTV for people counting from objects recorded by a camera. Currently, the process of detecting and tracking people takes a long time to detect all frames. In this study, the frame selection into keyframes uses the mutual information entropy method. The keyframes processing uses the Histogram of Oriented Gradient (HOG) and Kalman filter methods. The proposed method results F1 value of 0.85, recall of 76 %, and precision of 97 % with winStride parameter (12,12), scale 1.05, and the distance of the human object to CCTV 4 meters.

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