نشریه نوآوری های فناوری اطلاعات و ارتباطات کاربردی
پیاپی 3 (پاییز 1400)

The structure of operators in most traditional multi-objective evolutionary algorithms are based on fixed heuristics such as intersection and mutation, which are unable to learn the structures or properties of problems to create. To use evolutionary algorithms to learnability, news of evolutionary algorithms with the model is presented. In model evolutionary algorithms, innovative operators are replaced by machine learning models such as instructional and sample models. In this paper, a multi-objective evolutionary algorithm with a model is presented in which in each generation, a probable area of the search space deserves the model as a possible model. In the decision area in the search space, which are the dominant points, they are better ranked, we have clustered or different fuzzy methods, or on other points with the first order, it is a contest selection action. If you are missing, you take the form to be removed at close range, and the result is considered to be the center of the clusters, and then, clustering is done based on the nearest neighbors. The principal component analysis algorithm, which is the best method for reducing the given dimensions linearly, has been used for the models. New solutions are obtained from the model if it is a normal distribution. The proposed method is tested and the results are compared with the method of non-dominated sorting genetic algorithms. The results show that this method is faster than earlier methods and with fewer repetitions and evaluation of functions, the results are better and bold.

Today, IoT-related technologies are used in various devices, such as control devices that have millions of nodes, each of which is based on specific platforms. This method offers a method that works better than well-known routing protocols such as H-LEACH, which is very energy efficient. In this proposed method, the nodes are divided into three areas, in which one of these areas sends packets directly to the workstation, and the other areas send packets in clusters. The Biogeography based optimization Algorithm is used in the selection of cluster nodes in this method. The proposed method was compared with proposed methods such as H-LEACH and SEP.

In this study, the accuracy of daily rain prediction by two methods including DeepESN neural network and Linear multivariate regression has been compared. For this reason, actual data for rain and other affective parameters by daily distance time and thirty years has been received from the Hormozgan climate organ and has been analyzed by two methods. This data is from Bandar Abbas, Minab, and Qeshm cities, and because of short distance of these cities before entering data to DeepESN neural network and linear multivariate regression has been averaged. Demodulation for DeepESN in Matlab and linear multivariate regression in SPSS has been done. At the end of processing, results show that the daily rain forecasting model in DeepESN neural network has higher accuracy compared with the model produced with linear multivariate regression and have received better results for the DeepESN forecasting model by using estimation functions.

Organizational resource planning systems are integrated systems that affect all aspects of the organization. These systems are one of the largest and most sophisticated software products in the world, providing significant functionality and management capability for the organization. The purpose of this study is to investigate the effect of organization resource planning system on on resource optimization and saving time in managing administrative services and support

The study population consisted of 130 managers, experts and employees of Sepehr Kish Techno Energy Management Support Office. The sample of this research is selective and non-probable. In this study field and library method were used for data collection and questionnaire was used as the tool. Statistical analysis was performed using SPSS software.

The research results show a positive and significant effect of the organization's resource planning system on resource optimization and time saving and unlimited transfer of information productivity in Sepehr Kish Techno Energy Company.

In the present study, the organization's resource planning system was recognized as an important and effective factor in optimizing resources and saving time and transferring information indefinitely in urinary services and support.

The flocking of fish or birds can be modeled with multiagent systems. Likewise, their flocking behavior arises from three simple rules developed by Craig Reynolds, including separation, alignment, and cohesion. This paper aims to design a controller to deliver postal packages of an area or district using a group of Unmanned Aerial vehicles (UAVs). To accomplish this task, consider multiple groups of UAVs with distinct leader-follower controllers using formation control to deliver the postal packages to desired areas. In each group of UAV agents, it exists one leader and multiple follower agents in which the number of leader agents in each group is equal to the number of existing groups. The leader of each group establishes communication between these groups. According to Reynolds rules, the flocking controller is a good choice for the leader agents. A virtual leader agent accompanies the proposed flocking controller in this paper. The leader UAV agents will follow the virtual leader using the flocking controller by controlling this virtual agent. The advantages of the proposed method include low computational complexity, short computational time, high processing speed, low bandwidth, cost efficiency, and easy implementation. Simulation results show the proposed controller's fault tolerance ability in case one faulty follower-leader agent exists in the closed-loop system.

Obfuscation in the general sense is a technique that makes it more difficult to read and analyze the code of a program, which is done for the purpose of software security. For reverse engineering, a control flow graph is commonly used. As a result, this graph of the control flow must be obfuscated in some way. In this paper, the control flow graph using multi-threaded petri nets with a hierarchical selector is obscured. The main discussion is about dividing the code into sections so that the program runs in separate threads. These threads should be managed by the thread manager so that there is no problem in executing them. The more complex the petri net used to model the program, the more difficult it is to reverse engineering. The slightest change in the execution process by using stopping points affects the selection of the hierarchical selector, and as a result, the program does not go through its main process.