applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. artificial neural networks (ann) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. most ann models applied in economics use the gradient descent method as their learning algorithm. however, t...

optimizing the database queries is one of hard research problems. exhaustive search techniques like dynamic programming is suitable for queries with a few relations, but by increasing the number of relations in query, much use of memory and processing is needed, and the use of these methods is not suitable, so we have to use random and evolutionary methods. the use of evolutionary methods, beca...

in recent years, significant research efforts have been devoted to the optimal planning of power systems. substation expansion planning (sep) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future demand. the large number of design variables, and combination of discrete ...

Injection molding is one of the most important and common plastic formation methods. Combination of modeling tools and optimization algorithms can be used in order to determine optimum process conditions for the injection molding of a special part. Because of the complication of the injection molding process and multiplicity of parameters and their interactive effects on one another, analytical...

in this paper a scheduling problem in a 2-stage supply chain is discussed. suppliers are in the first stage and in the second stage, there are vehicles which carry orders to a manufacturing center. the purpose is to allocate orders to suppliers, sequence the suppliers’ production, allocate orders to transport vehicles and prioritize orders that should be carried by vehicles to minimize the tota...

Nowadays, Robots account for most part of our lives in such a way that it is impossible for usto do many of affairs without them. Increasingly, the application of robots is developing fastand their functions become more sensitive and complex. One of the important requirements ofRobot use is a reliable software operation. For enhancement of reliability, it is a necessity todesign the fault toler...

bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. therefore, correct prediction of bankruptcy is of high importance in the financial world. this research intends to investigate financial crisis prediction power using models based on neural network...

Search-based optimization methods have been used for software engineering activities such as software testing. In the field of software testing, search-based test data generation refers to application of meta-heuristic optimization methods to generate test data that cover the code space of a program. Automatic test data generation that can cover all the paths of software is known as a major cha...

The objective of this paper is path planning of a 3 DOF planer robot with hydraulic actuator using genetic algorithm. First the geometric and kinematic parameters of robot were established. The equations of motion are derived by Lagrange method. We proposed the model for proportional valve and hydraulic actuators. Then using the genetic algorithm we minimized the hydraulic energy consumption as...