Modeling and Optimization of M-cresol Isopropylation for Obtaining N-thymol: Combining a Hybrid Artificial Neural Network with a Genetic Algorithm

The application of a hybrid framework based on the combination, artificial neural network-genetic algorithm (ANN-GA), for n-thymol synthesis modeling and optimization has been developed. The effects of molar ratio propylene/cresol (X1), catalyst mass (X2) and temperature (X3) on n-thymol selectivity Y1 and m-cresol conversion Y2 were studied. A 3-8-2 ANN model was found to be very suitable for reaction modeling. The multiobjective optimization, led to optimal operating conditions (0.55 ≤X1≤0.77; 1.773 g ≤ X2 ≤1.86 g; 289.74 °C ≤ X3 ≤291.33 °C) representing good solutions for obtaining high n-thymol selectivity and high m-cresol conversion. This optimal zone corresponded to n-thymol selectivity and m-cresol conversion ranging respectively in the interval [79.3; 79.5]% and [13.4 %; 23.7]%. These results were better than those obtained with a sequential method based on experimental design for which, optimum conditions led to n-thymol selectivity and m-cresol conversion values respectively equal to 67%and 11%. The hybrid method ANN-GA showed its ability to solve complex problems with a good fitting

Forecasting the role of public expenditure in economic growth Using DEA-neural network approach

This paper integrates data envelopment analysis (DEA) and artificial neural networks (ANN) to forecast the role of public expenditure in economic growth in OCDE countries. The results show that this approach is a powerful and appropriate method to forecast this role. DEA method allows us to develop a neutral evaluation, unbiased a priori by any type of criteria, of the proportions in which the goal of productive spending is pursued, for any expenditure. Then we apply ANN to forecast economic growth by using input data taken at frontier. At the end of the DEA-ANN chain, prediction-power tests appear positive: best structures of multiple hidden layers indicate more ability to forecast according to best structures of single hidden layer but the difference between those is not much.DEA method; Economic growth; Public expenditure; Artificial neural network; OCDE countries

Efficiency Considering Credit Risk in Banking Industry, Using Two-stage DEA

The increased competition in the banking industry and banks' efforts to participate in new markets has affected bank performance and credit risk. Their presence in new markets and strong competition from other competitors today makes them face more uncertain situation. Given the importance of this issue, there are few studies about the efficiency calculated with regard to credit risk. Banking literature on this subject is poor. This paper introduces two-stage data envelopment analysis technique for estimation of their efficiency with regard to credit risk, its output and inputs in the first and second stage. Non-performing loans is output to proxy credit risk

Measuring the Technical Efficiency of the Banking Sector (Economic Growth in Ghana)

This study assesses the technical performance and overall productivity change factor after consolidation and the subsequent system of banking reforms to stabilize the sector before the effects of the financial crisis. The study uses both non-parametric data wrapping (DOS) and the Stochastic Boundaries (SFA) parametric approach using the Malmquist Productivity Index and the Fault Component Production Function to determine whether there has been a significant change in efficiency in a sample of 12 banks representing about 80 percent of Ghana's total bank assets. The theoretical approach of the remedy is used when selecting input and output variables. The input variables to be included are total deposits, total capital and operating costs, including staff costs, and production variables are loans and operating income that are responsible for weighted returns, such as interest income or cost-based revenues. The results suggest that the average technical efficiency within the SFA and the general change in production, per the factor of productivity at the DEA will decrease as bank production shifts to interest-only income or cost-based revenues. Although the size is different, both the SFA and DEA are managing in a similar direction for technical efficiency and overall factoring production. The impact of the study suggests that policymakers should be concerned about the bank's ability to arbitrarily generate cost-based revenues, which is a high long-term cost to the banking system. Keywords: Data Envelopment Analysis, Malmquist productivity index, technical efficienc

Combining efficiency with ROA: indicator of future relative performance - South African banking groups

Bank financial performance and relative future financial performance are important issues to stakeholders like management, shareholders, investment analysts and portfolio managers. This paper provides evidence that bank financial performance expressed as return on assets (ROA) figures that are adjusted according to relative income and expenditure efficiency provide fundamental measures of performance that have a causal link with future profits and can be utilised in estimating future financial performance. The methodology applied in this research consists of empirically investigating the annual changes in the ROAs of the nine listed South African Banking Groups over the period 2000 to 2008. The study consists of a two stage process. Data envelopment analysis (DEA) is conducted and resultant DEA scores are combined with the calculated ROAs of banks to provide efficiency adjusted ROA. The findings of this research paper shows that combining the CRS efficiency of bank groups with ROA provides a more reliable measure of future financial performance than just conventional ROA figures and efficiency figures

A Review of Measuring the Efficiency of Financial Institutions: A DEA Approach

The management of a financial institution, like any other company, requires the use of a certain number of indicators. The first indicators to be monitored are activity and profitability indicators, then we move on to ratio analysis. The analysis of ratios has shown a certain number of limitations. Efficiency analysis has just filled in the gaps and especially the use of data envelopment analysis. This paper seeks to highlight the salient aspects surrounding the study of efficiency in financial institutions. The paper focuses on the works that have mobilized the data envelopment method in different economic spaces. The objective is to highlight the factors that have an impact on the measured efficiency, and whether these factors are common to all the studies analyzed in this paper. The comparative study shows that technical efficiency is positively impacted by the size and history of the financial institution. However, it is not significantly affected by geographic location

A Review of Measuring the Efficiency of Financial Institutions: A DEA Approach

The management of a financial institution, like any other company, requires the use of a certain number of indicators. The first indicators to be monitored are activity and profitability indicators, then we move on to ratio analysis. The analysis of ratios has shown a certain number of limitations. Efficiency analysis has just filled in the gaps and especially the use of data envelopment analysis. This paper seeks to highlight the salient aspects surrounding the study of efficiency in financial institutions. The paper focuses on the works that have mobilized the data envelopment method in different economic spaces. The objective is to highlight the factors that have an impact on the measured efficiency, and whether these factors are common to all the studies analyzed in this paper. The comparative study shows that technical efficiency is positively impacted by the size and history of the financial institution. However, it is not significantly affected by geographic location

Sharepricing of South African banking groups: importance of efficiency and earnings per share

Previous research findings indicate that the relevant performance of firms is one way or another, reflected in the market prices of shares. Such research is focussed on different performance components of firm individual risk (FIR), but none of the research segregates systematic and unsystematic risk of the shares to levels where the relative FIR components that were researched could be quantified in proportion to FIR level share price determinants. This brings about the objective of this research to segregate the pricing of shares in terms of market and firm specific factors with the intention to quantify the association of relative bank efficiency and earnings performance with the pricing of South African bank shares. The study draws a parallel between the actual significance of measured efficiency and earnings per share (EPS) with share pricing and quantified FIR. Within this context the comparative significance of measured efficiency and EPS are explored to investigate the Efficient Market Hypothesis (EMH) prevalence. An analysis of efficiency and share price relationships at different financial year time points shows a semi-strong form of the EMH in both the pre-Global Financial Crises (GFC) and GFC periods. This indicates that the application of an active investment strategy by investors based on efficiency measures may be beneficial. The impact of EPS as contributing determinant of share prices increased during the GFC period compared to the pre-GFC period, but reflects a strong form of the EMH

Efficiency Predictions by Fuzzy Piecewise Auto-regression in Dynamic Network System

Workshop 2015 -Advances in DEA Theory and Applications (December 1-2, 2015)Since efficiency prediction can help managers to monitor future performance and detect potential failures, it is important for production and operation management. Data envelopment analysis is comprehensively applied to evaluate the relative performance in various areas. However, only few studies try to forecast the relative performance estimated by data envelopment analysis. We propose a performance forecasting model that integrates the multi-activity dynamic network data envelopment analysis and fuzzy piecewise auto-regression. The proposed approach constructs a dynamic performance measurement with the network structure to calculate the catching-up efficiency index. The catching-up efficiency index is further decomposed into the technical efficiency change and dynamic efficiency change to capture the effect of carry-over items. The fuzzy piecewise auto-regression is applied to regress the possibility and necessity estimation models by catching-up efficiency index for forecasting efficiency. In this paper, a data from banks in Taiwan from 2006 to 2012 are applied. The results indicate that the proposed approach has highly accuracy rate.The workshop is supported by JSPS (Japan Society for the Promotion of Science), Grant-in-Aid for Scientific Research (B), #25282090, titled “Studies in Theory and Applications of DEA for Forecasting Purpose.本研究はJSPS科研費 基盤研究(B) 25282090の助成を受けたものです

Forecasting the role of public expenditure in economic growth Using DEA-neural network approach

This paper integrates data envelopment analysis (DEA) and artificial neural networks (ANN) to forecast the role of public expenditure in economic growth in OCDE countries. The results show that this approach is a powerful and appropriate method to forecast this role. DEA method allows us to develop a neutral evaluation, unbiased a priori by any type of criteria, of the proportions in which the goal of productive spending is pursued, for any expenditure. Then we apply ANN to forecast economic growth by using input data taken at frontier. At the end of the DEA-ANN chain, prediction-power tests appear positive: best structures of multiple hidden layers indicate more ability to forecast according to best structures of single hidden layer but the difference between those is not much