The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation platforms. Therefore, GAMA modelling and simulation platform is designed to facilitate the development of spatialized, multi-paradigms and multi-scale models to address this challenge.This platform enables modelers to build explicit and multi-level models geographically (spatially). It includes notably effective Data Mining models and Geographic Information Systems (GIS) that make the effort to model and analyze easier. This study examines how this platform deals with these concerns and how modeler's tools are provided from the box. Also, shows its skills relating to the tight combination of 3D visualization, GIS data management, and multi-level modeling. Furthermore, several examples of GAMA-based projects that had been built for complex models.
This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue
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Due to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor i
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In this study, structures damage identification method based on changes in the dynamic characteristics
(frequencies) of the structure are examined, stiffness as well as mass matrices of the curved
(in and out-of-plane vibration) beam elements is formulated using Hamilton's principle. Each node
of both of them possesses seven degrees of freedom including the warping degree of freedom. The
curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory
in 1994. A computer program was developing to carry out free vibration analyses of the curved
beam as well as straight beam. Comparing with the frequencies for other researchers using the general
purpose program MATLAB. Fuzzy logic syste
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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Polarization is an important property of light, which refers to the direction of electric field oscillations. Polarization modulation plays an essential role for polarization encoding quantum key distribution (QKD). Polarization is used to encode photons in the QKD systems. In this work, visible-range polarizers with optimal dimensions based on resonance grating waveguides have been numerically designed and investigated using the COMSOL Multiphysics Software. Two structures have been designed, namely a singlelayer metasurface grating (SLMG) polarizer and an interlayer metasurface grating (ILMG) polarizer. Both structures have demonstrated high extinction ratios, ~1.8·103 and 8.68·104 , and the bandwidths equal to 45 and 55 nm for th
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Transportation and distribution are the most important elements in the work system for any company, which are of great importance in the success of the chain work. Al-Rabee factory is one of the largest ice cream factories in Iraq and it is considered one of the most productive and diversified factories with products where its products cover most areas of the capital Baghdad, however, it lacks a distribution system based on scientific and mathematical methods to work in the transportation and distribution processes, moreover, these processes need a set of important data that cannot in any way be separated from the reality of fuzziness industrial environment in Iraq, which led to use the fuzzy sets theory to reduce the levels of uncertainty.
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
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