Performance Analysis of Simulated Annealing and Genetic Algorithm on systems of linear equations

Problem solving and modelling in traditional substitution methods at large scale for systems using sets of simultaneous equations is time consuming. For such large scale global-optimization problem, Simulated Annealing (SA) algorithm and Genetic Algorithm (GA) as meta-heuristics for random search technique perform faster. Therefore, this study applies the SA to solve the problem of linear equations and evaluates its performances against Genetic Algorithms (GAs), a population-based search meta-heuristic, which are widely used in Travelling Salesman problems (TSP), Noise reduction and many more. This paper presents comparison between performances of the SA and GA for solving real time scientific problems. The significance of this paper is to solve the certain real time systems with a set of simultaneous linear equations containing different unknown variable samples those were simulated in Matlab using two algorithms-SA and GA. In all of the experiments, the generated random initial solution sets and the random population of solution sets were used in the SA and GA respectively. The comparison and performances of the SA and GA were evaluated for the optimization to take place for providing sets of solutions on certain systems. The SA algorithm is superior to GA on the basis of experimentation done on the sets of simultaneous equations, with a lower fitness function evaluation count in MATLAB simulation. Since, complex non-linear systems of equations have not been the primary focus of this research, in future, performances of SA and GA using such equations will be addressed. Even though GA maintained a relatively lower number of average generations than SA, SA still managed to outperform GA with a reasonably lower fitness function evaluation count. Although SA sometimes converges slowly, still it is efficient for solving problems of simultaneous equations in this case. In terms of computational complexity, SA was far more superior to GAs.

Optimal Fitting Method of Nonlinear Simultaneous Equations Considering Structural Tensor Image Modeling

For the purpose of resolving the phenomenon of network congestion in the process of many-to-one communication in multimedia networks at present, the optimal fitting method of nonlinear simultaneous equations (OFMNSEs) is applied to the multimedia transmission congestion control system in this paper. The rate control and resource scheduling are effectively combined, and a clustering network structure is used to activate the congestion control method in turn based on the cluster header and intracluster-related indexes. Finally, it can be known through the analysis of the simulation results that the OFMNSE algorithm put forward in this paper can improve the congestion issue of the multimedia network transmission process and reduce the packet loss rate of data during the transmission effectively under the condition of different relative cache sizes compared with the conventional algorithm.

Comparison Between Nelson-Olson Method and Two-Stage Limited Dependent Variables (2SLDV ) Method for the Estimation of a Simultaneous Equations System (Tobit Model)

This study relates to the estimation of a simultaneous equations system for the Tobit model where the dependent variables ( ) are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method and Two- Stage limited dependent variables(2SLDV) method to get of estimators that hold characteristics the good estimator . That is , parameters will be estimated for the limited variables and find the variance-covariance matrix for extracted estimators by the aforementioned two methods and then compare between the results of the two methods and find any better method by estimation and then finding the estimation efficiency, and this is what the study aims to . A simultaneous equations system will be imposed for the limited model defined by two equations containing two endogenous variables one of complete observations and the other censored at zero. The two methods were used to analyze the relationship between income and family expenditure on durable consumer goods , where the results showed that the performance of (Nelson-Olson) method is better than performing the Two-Stage limited dependent variables (2SLDV) method in obtain the lower values and all comparison measures as well as the results showed that income and expenditure one affects the other and the and the price affects the income and expenditure

Public Capita and Growth: The Role of Institutions in Development

This study analyzes the links between public capital and growth using an econometric model of simultaneous equations, estimated on a panel of forty-three developing countries over the period 2003-2020. This growth model explains the determinants of GDP and public and private capital stocks. The accumulation of public, private and human capital generates externalities that are sources of endogenous growth. However, the formation of public capital generated a crowding out effect, to the detriment of that of private capital, because of differentiated budgetary constraints. Our results show that several developing countries have moved away from an optimal structure for the growth of sharing of available capital between the public and private sectors. In doing so, are institutions a prerequisite for the economic development of African countries.

Financial inclusion, corporate social responsibility and firm performance – analysis of interactive relationship

Purpose Prior studies on corporate social responsibility (CSR) and performance have frequently used unidirectional, single-equation regression although the literature recommends the reciprocal association of CSR with firm performance. This paper aims to elucidate the interactive relationship of CSR spending with financial inclusion (FI) and firm performance. The study also explores the moderating impact of the level of FI on the CSR-firm performance relationship. Design/methodology/approach This study uses a simultaneous equations model to capture the FI, CSR and firm performance relationships and apply a three-stage regression approach and generalised method of moments approach to address possible endogeneity. Findings The results confirm a positive association of CSR spending with performance but a negative relationship of FI with performance. This paper also finds that FI negatively moderates the CSR spending-performance relationship. Practical implications The positive impact of CSR spending and the negative impact of FI on performance in mandatory CSR regimes provides valuable input in policy formulation. The results of the study will also be useful to national and international organisations, such as the International Monetary Fund and the World Bank. Originality/value This study uses a simultaneous equations model to capture the reciprocal association of CSR spending with firm performance, whereas prior studies on CSR and performance have frequently used unidirectional, single-equation regression. This paper also finds that FI negatively moderates the CSR spending- performance relationship. Including FI and exploring the moderating impact of the level of FI on the CSR-firm performance relationship is novel.

The interactive relationship between water environmental pollution and the quality of economic growth in China: An empirical research based on the dynamic simultaneous equations model

As the Chinese economy enters the stage of new normal, high-quality economic development has become the current priority. Economic development should not be achieved at the cost of environment and resources. Clarifying the interactive relationship between water environment pollution and the quality of economic growth can help realize water environment protection and sustainable economic development. Based on the data of 30 provinces and cities in China, this paper studies the bidirectional mechanism between water environmental pollution and the quality of economic growth with the dynamic simultaneous equations model. The paper concludes that environmental pollution and the quality of regional economy growth have strong hysteretic nature; And that water environmental pollution and the development of regional economy display the relationship of bidirectional feedback. Discharge of pollutants into the water environment can inhibit high-quality development of regional economy. As the intensity of water environmental pollution increases by 1%, the quality of regional economic growth decreases by 0.0230%; Hence as the quality of regional economic growth increases by 1%, the intensity of water environmental pollution increases by 0.148%. Therefore, sustainable economic development should be attached with due significance, by removing the factors of environmental pollution, timely adjusting environmental policies, and promoting harmony between ecological environment and economic growth.