J. Comp. & Math. Sci. Vol.4 (2), 102-104 (2013)
Simulation of the Income of the Behavioral Model RAJESH SONI Lecturer, B.N.P.G. Girls’ College, Udaipur, INDIA. (Received on: March 6, 2013) ABSTRACT Simulation is a way to study the behavior of various models. In this paper the salary data of college have been taken .after preparing the composite index regression is applied. Then freeware software Simulation 4.0 is used for the Simulation. Keywords: Simulation, college data set, Simulation 4.0 etc.
1. COMPUTER SIMULATION Simulation means representing certain key characteristics or behaviors of a selected physical or abstract system. Computer simulation means to develop a model of real- life or hypothetical situation on a computer so that it can study to see how the systems work by changing variables. Computer simulation is useful part of modeling many natural systems. In simulation, the behavior of model is changed according to the set of initial parameters assumed for the environment. The formal modeling of system is via mathematical model. In this we attempt to find analytical solutions enabling the prediction of the behavior of the system from a set of parameters & initial condition.
taken for the simulation. There are 86 instances of staff including all categories. The attributes’ are qualification, sex, post, salary, data of birth, age, experience. For preparing the composite index ranked are given to attributes Qualification, Post, Age & experience. By this index of Qualification, Post, Age & experience are created. By giving equal weight age to all, composite index is prepared. For example the ranking of Post is given. S.No. 1 2 3 4 5 6
2. COLLEGE DATA SET
7
Bhupal Nobles’ Post Graduation College, Udaipur2 staff salaries have been
8 9
Post Acting Principal Vice Principal Lecturer Regular Adhoc Lecturer Adhoc Lecturer Junior Accountant, Lab Assistant, Demonstrator Temporary LDC, Temporary Lab Assistant Lab Boy, Peon, Watch Man Temporary Peon
Journal of Computer and Mathematical Sciences Vol. 4, Issue 2, 30 April, 2013 Pages (80-134)
Rank 9 8 7 6 5 4 3 2 1
103
Rajesh Soni, J. Comp. & Math. Sci. Vol.4 (2), 102-104 (2013)
For example the ranking of Qualification is given. S.No. 1 2 3 4 5 6 7
Qualification 8 12 B.A.,B.Com.,B.Sc. M.A.,M.Com.,M.Sc.,M.Lib., MBA,MCA,B.E. M.Phil, M.Tech. P.HD. NET, SLET
Rank 1 5 6 7 8 9 10
After this weight age of attribute post is created. Similarly Index is created for attributes Age & experience. In last by giving equal weight age composite index is created.
3. REGRESSION Multiple regressions are a technique that allows us to predict value on one variable on the basis of values of other variables. There is two variable composite index & salary. The composite index is independent variable. Using regression following equation is found Gross Salary=290.3017*composite index12338.1 4. SIMULATION 4.0 SOFTWARE[1] This software is provided 'as-is', without any express or implied warranty. The snapshot of software is given below
Figure 1 Simulation 4.0 software
For simulation the composite index is taken as input. The normal distribution is used. The following formula is used. =Simula_Normal (90.68094455, 30.94123495,"composite index") After calculation value 90.68094 is received. By using this value Output is calculated by entering this formula =290.337923069947*F212361.7+simula_output ("salary") 5. RESULT The simulation result is hereby given
Figure 2 Simulation result Journal of Computer and Mathematical Sciences Vol. 4, Issue 2, 30 April, 2013 Pages (80-134)
Rajesh Soni, J. Comp. & Math. Sci. Vol.4 (2), 102-104 (2013)
104
In the above output for the various simulated value of composite index the salary is predicted. There are total 100 iterations.
7. CONCLUSION
6. ANALYSIS
predicted. The simulated value can be used
S.No. 1
2
3 4
Properties Salary
Composite index Regression slope Regression Constant
Remark Maximum value 32242.57112, Mean value 13022.04342 Maximum value 153.5666898, Mean value 87.357 290.3017
Using simulation tool, on the basis of composite index the value of salary is
for the calculation of expenditure on salary. REFERENCES 1. JosĂŠ Ricardo Varela, http://www.ucema.edu.ar/u/jvarela/index _eng.htm.
-12338.1
2. B.N.P.G. Girls’ College, Udaipur.
Journal of Computer and Mathematical Sciences Vol. 4, Issue 2, 30 April, 2013 Pages (80-134)