One problem in simulating crowds in traditional markets is calculating the interaction duration between traders and buyers. This problem can be solved in a simple way by doing field observation to obtain some samples to find the average interaction duration between traders and buyers. This method is simple. On the other hand, the result will be less valid if the parameters are change. The purpose of this research is to develop an interaction model between traders and buyers by looking deeper into the negotiation process. This model is developed based on multi-agent system. Output of this model is the interaction duration. This model has been implemented in a traditional market crowd simulation. Based on the simulation, by adjusting the parameters in this model, the interaction duration by the model matches the real condition in traditional markets.

In this article an investigation into search operations for the multiplicative inverse in the ring of integers modulo m for Error Control Coding tasks and for data security is shown. The classification of the searching operation of the multiplicative inverse in the ring of integers modulo m is provided. The best values of parameters for Joye-Paillier method and Lehmer algorithm were also found. The improved Bradley modification for the extended Euclidean algorithm is also offered, which gives the operating speed improvement for 10-15%. The integrated experimental research of basic classes of searching methods for multiplicative inverse in the ring of integers modulo m is conducted for the first time and the analytical formulas for these calculations of random access memory necessary space when operated at k-ary RS-algorithms and their modifications are shown.

A novel method of monitoring the quality i.e. the percentage of purity of diesel fuel in real-time environment in smart vehicles is presented here. The method incorporates temperature compensated density measurement using a dual load cell and temperature sensor. The mass of the small fixed volume of diesel sample and temperature of diesel are measured by the pre-calibrated load cell based amplifier set up and a smart miniature temperature sensor respectively. The amplified voltage of the load cell provides the measure of the density of the fuel. Further, the measured value of fuel density is temperature compensated and compared with standard reference values to indicate percentage of purity of the diesel sample. The method is automated with an intelligent virtual instrument that provides all the means of testing the fuel sample and displaying results with high level of accuracy ~ 99.8 %. The model offers a way of providing vital real time information to user and has great future prospects. Also, the data collected can be analyzed for developing complex mathematical models to suggest optimized driving parameters for vehicles.

Highly-interconnected Hopfield network with Content Addressable Memory (CAM) are shown to be extremely effective in constraint optimization problem. The emergent of the Hopfield network has producing a prolific amount of research. Recently, 3 Satisfiability (3-SAT) has becoming a tool to represent a variety combinatorial problems. Incorporated with 3-SAT, Hopfield neural network (HNN-3SAT) can be used to optimize pattern satisfiability (Pattern-SAT) problem. Hence, we proposed the HNN-3SAT with Hyperbolic Tangent activation function and the conventional McCulloch-Pitts function. The aim of this study is to investigate the accuracy of the pattern generated by our proposed algorithms. Microsoft Visual C++ 2013 is used as a platform for training, testing and validating our Pattern-SAT design. The detailed performance of HNN-3SAT of our proposed algorithms in doing Pattern-SAT will be discussed based on global pattern-SAT and running time. The result obtained from the simulation demonstrate the effectiveness of HNN-3SAT in doing Pattern-SAT.

Krill herd algorithm (KHA) is a novel nature inspired (NI) optimization technique that mimics the herding behavior of krill, which is a kind of fish found in nature. The mathematical model of KHA is based on three phenomena observed in the behavior of a herd of krills, which are, moment induced by other krill, foraging motion and random physical diffusion. These three key features of the algorithm provide a good balance between global and local search capability, which makes the algorithm very powerful. The objective is to minimize the distance of each krill from the food source and also from the point of highest density of the herd, which helps in convergence of population around the food source. Improvisation has been made by introducing neighborhood distance concept along with genetic reproduction mechanism in basic KH Algorithm. KHA with mutation and crossover is called as (KHAMC) and KHA with neighborhood distance concept is referred here as (KHAMCD). This paper compares the performance of the KHA with its two improved variants KHAMC and KHAMCD. The performance of the three algorithms is compared on eight benchmark functions and also on two real world economic load dispatch (ELD) problems of power system. Results are also compared with recently reported methods to establish robustness, validity and superiority of the KHA and its variant algorithms.

The intelligent control system design has been changed from the conventional approach to the optimization framework solved by efficient metaheuristics. The intensified current search (ICS) has been recently proposed as one of the most powerful metaheuristics for solving optimization problems. The ICS, the latest modified version of the conventional current search (CS), possesses the memory list (ML) regarded as the exploration strategy and the adaptive radius (AR) and adaptive neighborhood (AN) mechanisms regarded as the exploitation strategy. The ML is used to escape from local entrapment caused by any local solution, while both AR and AN mechanisms are conducted to speed up the search process. In this paper, the application of the ICS to multiobjective PID controller design optimization for the three-phase induction motor (3-IM) speed control system is proposed. Algorithms of the ICS and its performance evaluation against multiobjective functions are presented. As simulation results, the ICS can provide very satisfactory solutions for all test functions and the 3-IM control application. Moreover, the simulation results of motor control application are confirmed by the experimental results based on dSPACE technology.

Cloud computing has its characteristics along with some important issues that should be handled to improve the performance and increase the efficiency of the cloud platform. These issues are related to resources management, fault tolerance, and security. The purpose of this research is to handle the resource management problem, which is to allocate and schedule virtual machines of cloud computing in a way that help providers to reduce makespan time of tasks. In this paper, a hybrid algorithm for dynamic tasks scheduling over cloud's virtual machines is introduced. This hybrid algorithm merges the behaviors of three effective techniques from the swarm intelligence techniques that are used to find a near optimal solution to difficult combinatorial problems. It exploits the advantages of ant colony behavior, the behavior of particle swarm and honeybee foraging behavior. Experimental results reinforce the strength of the proposed hybrid algorithm. They also prove that the proposed hybrid algorithm is the best and outperformed ant colony optimization, particle swarm optimization, artificial bee colony and other known algorithms.

In this paper, according to the structure char-acteristics of steer-by-wire (SBW) system for the TFC20 electric forklift, steering dynamics model and two degree of freedom vehicle model are deduced for SBW forklift. Aiming at the free design features of the angular trans-mission characteristics in the SBW system of electric forklift, the theory of active steering control strategy is studied. After analyzing the influence factors of the an-gular transmission ratio of the steering system, the ideal angular transmission ratio is proposed, which is based on the yaw rate gain invariance. Also, the control strategy of the yaw rate feedback and the full state feedback is stud-ied. The simulation results show that the above strategy is effective for the active steering control; it can improve the operating stability and the response speed of the fork-lift.