scholarly journals Computer Intelligent Test Paper System Based on Genetic Algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 134
Author(s):  
Hongming Wang
Keyword(s):  
Genetic Algorithm ◽  
Rapid Development ◽  
Standard Test ◽  
System Structure ◽  
Test Paper ◽  
Test Question ◽  
Main Method ◽  
Network Function ◽  
Online Examination ◽  
Crossover And Mutation

The rapid development of the Internet has brought tremendous changes to people’s lives. Through the network function, the online examination is gradually accepted by various educational and teaching institutions. Currently, online exams have become the main method of teaching evaluation. In order to solve the problem of intelligent test paper more effectively, this paper proposes a mufti-threaded intelligent test paper strategy based on genetic algorithm, and designs the computer system structure in the standard test question bank. Convergence simulation and experimental results show that the algorithm is better than simple particle swarm optimization algorithm, simple genetic algorithm and its improved algorithm. Established a mathematical model and objective function for test paper composition, and proposed an intelligent test paper composition strategy based on genetic algorithm. The investigator used overall coding, crossover and mutation operations to improve the global optimization capability and convergence speed. It overcomes the phenomenon of premature and improves the accuracy and speed of convergence. It has the advantages of strong optimization ability and good stability.

Strategy for Test Paper Composition Based on Genetic Algorithm

2014 ◽  
Vol 513-517 ◽  
pp. 1688-1691
Author(s):  
Hong Tao Tang
Keyword(s):  
Genetic Algorithm ◽  
Computer Network ◽  
Rapid Development ◽  
Adaptive Genetic Algorithm ◽  
Test Paper ◽  
Examination System ◽  
Coding Schemes ◽  
Online Test ◽  
Online Examination ◽  
Elitist Strategy

Recently, with rapid development of computer/network technology and algorithms for composing test paper, cyber-based online examination system is a practically valuable hot research concern. In the paper, the mathematical model is created for solving problems with the online test paper composition system. Through comparative analysis of merits and shortcomings of various coding schemes, and to overcome the shortcoming that traditional genetic algorithms easily fall into premature convergence, it utilizes the adaptive adjustment method of dynamic parameters and elitist strategy to improve to develop the online test paper forming scheme based on adaptive genetic algorithm. For the selection of each parameter, simulation test is conducted to obtain the solution approximate to the best one.

Strategy and Applied Research of Multi-Constrained Model of Automatic Test Paper Based on Genetic Algorithm

2010 ◽  
Vol 37-38 ◽  
pp. 1223-1230 ◽  
Author(s):  
Zhi Feng Liu ◽  
Ji Shi ◽  
Jia Liu ◽  
Yang Li
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Applied Research ◽  
Genetic Manipulation ◽  
Initial Population ◽  
Test Paper ◽  
Examination System ◽  
Automatic Test ◽  
Online Examination ◽  
Constrained Model

Test paper problem is a typical multi-constrained objective optimization problem. By using genetic algorithm, this paper analyzes the initial population generation, the chromosome coding and its genetic manipulation, control parameters. Solving that by natural-coded genetic algorithm, improves test paper success rate and convergence rate. This genetic algorithm is applied successfully on NHibernate architecture, and developed "automatic test paper" Online Examination system.

scholarly journals Research on English Online Education Platform Based on Genetic Algorithm and Blockchain Technology

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Xuezhong Wu
Keyword(s):  
Genetic Algorithm ◽  
Online Education ◽  
Rapid Development ◽  
Test System ◽  
Examination System ◽  
Blockchain Technology ◽  
Online Test ◽  
Online Examination ◽  
Education Platform ◽  
Examination Process

Nowadays, with the rapid development of network technology, the online examination mode has gradually replaced the traditional paper examination mode. This paper introduces computer technology into English teaching and studies and designs an English online test system for English subjects. The system introduces the design module and introduces the genetic algorithm for analysis. By using the artificial intelligence of the genetic algorithm to analyze the examination process, the online examination system completes a series of tasks from questions to examination results, making the examination work intelligent, standardized, and highly efficient. At the same time, it also gives candidates greater fairness and flexibility, making the entire examination process more efficient and convenient.

Enterprise distribution routing optimization with soft time windows based on genetic algorithm

2021 ◽  
pp. 1-11
Author(s):  
Kaixian Gao ◽  
Guohua Yang ◽  
Xiaobo Sun
Keyword(s):  
Genetic Algorithm ◽  
Customer Satisfaction ◽  
Optimization Problems ◽  
Rapid Development ◽  
Time Windows ◽  
Theory And Practice ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
A Company

With the rapid development of the logistics industry, the demand of customer become higher and higher. The timeliness of distribution becomes one of the important factors that directly affect the profit and customer satisfaction of the enterprise. If the distribution route is planned rationally, the cost can be greatly reduced and the customer satisfaction can be improved. Aiming at the routing problem of A company’s vehicle distribution link, we establish mathematical models based on theory and practice. According to the characteristics of the model, genetic algorithm is selected as the algorithm of path optimization. At the same time, we simulate the actual situation of a company, and use genetic algorithm to plan the calculus. By contrast, the genetic algorithm suitable for solving complex optimization problems, the practicability of genetic algorithm in this design is highlighted. It solves the problem of unreasonable transportation of A company, so as to get faster efficiency and lower cost.

scholarly journals Optimization of spectrum sensing in cognitive radio using genetic algorithm

2012 ◽  
Vol 25 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Rashmi Deka ◽  
Soma Chakraborty ◽  
Sekhar Roy
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Rapid Development ◽  
Probability Of Detection ◽  
Radio System ◽  
Probability Of False Alarm ◽  
Space Allocation ◽  
Wireless Environment ◽  
Better Than

Spectrum availability is becoming scarce due to the rise of number of users and rapid development in wireless environment. Cognitive radio (CR) is an intelligent radio system which uses its in-built technology to use the vacant spectrum holes for the use of another service provider. In this paper, genetic algorithm (GA) is used for the best possible space allocation to cognitive radio in the spectrum available. For spectrum reuse, two criteria have to be fulfilled - 1) probability of detection has to be maximized, and 2) probability of false alarm should be minimized. It is found that with the help of genetic algorithm the optimized result is better than without using genetic algorithm. It is necessary that the secondary user should vacate the spectrum in use when licensed users are demanding and detecting the primary users accurately by the cognitive radio. Here, bit error rate (BER) is minimized for better spectrum sensing purpose using GA.

Simulation of the Pressure-Bearing Capacity Test Model in Architectural Decoration Design

2014 ◽  
Vol 716-717 ◽  
pp. 391-394
Author(s):  
Li Mei Guo ◽  
Ai Min Xiao
Keyword(s):  
Genetic Algorithm ◽  
Bearing Capacity ◽  
Test Method ◽  
Test Model ◽  
Improved Genetic Algorithm ◽  
Good Convergence ◽  
Mutation Operators ◽  
Process Pressure ◽  
Calculation Process ◽  
Crossover And Mutation

in architectural decoration process, pressure-bearing capacity test is the foundation of design, and is very important. To this end, a pressure-bearing capacity test method in architectural decoration design is proposed based on improved genetic algorithm. The selection, crossover and mutation operators in genetic algorithm are improved respectively. Using its fast convergence characteristics eliminate the pressure movement in the calculation process. The abnormal area of pressure-bearing existed in buildings which can ensure to be tested is added, to obtain accurate distribution information of the abnormal area of pressure-bearing. Simulation results show that the improved genetic algorithm has good convergence, can accurately test the pressure-bearing capacity in architectural decoration.

scholarly journals SCHEDULLING MODEL OF REPLENISHMENT AT SEA FOR STRICKING FORCE UNIT IN SEA OPERATION USING GENETIC ALGORITHM

JOURNAL ASRO ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 1
Author(s):  
Aris Tri Ika R ◽  
Benny Sukandari ◽  
Okol Sri Suharyo ◽  
Ayip Rivai Prabowo
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Time Windows ◽  
Lubricating Oil ◽  
Optimal Time ◽  
Routing Problem ◽  
Scheduling Model ◽  
Force Unit ◽  
Replenishment At Sea ◽  
Crossover And Mutation

Navy as a marine core in the defense force is responsible for providing security for realizing stability and security of the country.  At any time there was an invasion of other countries past through sea,  TNI AL must be able to break the enemy resistance line through a sea operation to obtain the sea superiority. But this time the endurance of Striking force Unit at only 7-10 days and required replenishment at sea to maximize the presence in the theater of operations to meet a demand of the logistics: HSD, Freshwater, Lubricating Oil, foodstuffs and amonisi. For the optimal replenishment at sea required scheduling model supporting unit to get the minimum time striking force unit was on node rendezvous. Replenishment at sea scheduling model for striking force unit refers to the problems Vehicle routing problem with time windows using Genetic Algorithms. These wheelbase used is roulette for reproduction, crossover, and mutation of genes. Genetic algorithms have obtained optimum results in the shortest route provisioning scenario uses one supporting unit with a total time of 6.89 days. In scenario two supporting unit with minimal time is 4.97 days. In the scenario, the changing of the node replenishment Genetic Algorithm also get optimal time is 4.97 days with two supporting units. Research continued by changing the parameters of the population, the probability of crossover and mutation that can affect the performance of the genetic algorithm to obtain the solution. Keywords: Genetic Algorithm, Model Scheduling, Striking Force unit

scholarly journals Vulnerability and risk assessment for operating system (OS) with framework STRIDE: comparison between VulnOS and Vulnix

2021 ◽  
Vol 23 (3) ◽  
pp. 1643
Author(s):  
Adityas Widjajarto ◽  
Muharman Lubis ◽  
Vreseliana Ayuningtyas
Keyword(s):  
Information Disclosure ◽  
Risk Estimation ◽  
Rapid Development ◽  
Denial Of Service ◽  
Cyber Attacks ◽  
Easy Access ◽  
Case Scenario ◽  
Worst Case ◽  
Network Function ◽  
The World

<p><span lang="EN-US">The rapid development of information technology has made security become extremely. Apart from easy access, there are also threats to vulnerabilities, with the number of cyber-attacks in 2019 showed a total of 1,494,281 around the world issued by the </span><span lang="EN-US">national cyber and crypto agency (BSSN) honeynet project. Thus, vulnerability analysis should be conducted to prepare worst case scenario by anticipating with proper strategy for responding the attacks. Actually, vulnerability is a system or design weakness that is used when an intruder executes commands, accesses unauthorized data, and carries out denial of service attacks. The study was performed using the AlienVault software as the vulnerability assessment. The results were analysed by the formula of risk estimation equal to the number of vulnerability found related to the threat. Meanwhile, threat is obtained from analysis of sample walkthroughs, as a reference for frequent exploitation. The risk estimation result indicate the 73 (seventy three) for the highest score of 5 (five) type risks identified while later on, it is used for re-analyzing based on the spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of prvilege (STRIDE) framework that indicated the network function does not accommodate the existing types of risk namely spoofing.</span></p>

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