In this paper a Neural Predictive Controller (NPC) designed to control a broad class of process systems. Neural network identification yields nonlinear global model of the unknown system. LevenbergMarquardt (L-M) optimization method is used to find optimal control signal to minimize future errors of the objective function of predictive controller. Inequality constraints of actuators are added t...

for a uniform distribution of water, decrease in water waste and decrease in erosion of soil, it is important that a land be prepared with proper slopes along its length as well as width. the aim of leveling is to create appropriate slopes for irrigation and drainage on the lands that were not already properly levelled and of the same time creating the level surface with a minimum transport of ...

in this paper, a stochastic cell formation problem is studied using queuing theory framework and considering reliability. since cell formation problem is np-hard, two algorithms based on genetic and modified particle swarm optimization (mpso) algorithms are developed to solve the problem. for generating initial solutions in these algorithms, a new heuristic method is developed, which always cre...

this study is investigated the optimum parameters for a tuned mass damper (tmd) under the seismic excitation. shuffled complex evolution (sce) is a meta-heuristic optimization method which is used to find the optimum damping and tuning frequency ratio for a tmd. the efficiency of the tmd is evaluated by decreasing the structural displacement dynamic magnification factor (ddmf) and acceleration ...

response surface methodology is a common tool in optimizing processes. it mainly concerns situations when there is only one response of interest. however, many designed experiments often involve simultaneous optimization of several quality characteristics. this is called a multiresponse surface optimization problem. a common approach in dealing with these problems is to apply desirability funct...

e-learning model is examined of three major dimensions. and each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. if any of these undetermined events be considered in the optimization process, t...

this paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. the model makes use of the newly introduced particle swarm optimization algorithm. a two step optimization model is developed and solved with the particle swarm optimization method. the model first carries out an exhaustive enumeration search for all feasible sets of p...

In this paper, we propose a new tool based on Observed Time Difference of Arrival (OTDOA) technique in order to estimate both the position of the different User Equipments (UEs) and the Relative Time Differences (RTDs) between Node Bs in real UMTS networks from measurements reports providing the TM parameter and the locations of the sites. This technique results in a non-linear least squares es...

Engineering optimization needs easy-to-use and efficient optimization tools that can be employed for practical purposes. In this context, stochastic search techniques have good reputation and wide acceptability as being powerful tools for solving complex engineering optimization problems. However, increased complexity of some metaheuristic algorithms sometimes makes it difficult for engineers t...