Multiple-deme parallel genetic algorithm based on modular neural network for effective load shedding

Gholami-Rahimabadi, Ali; Razmi, Hadi; Doagou‐Mojarrad, Hasan

doi:10.21203/rs.3.rs-390375/v1

Cited by 4 publications

(4 citation statements)

References 52 publications

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“…The process of student user login examination module is shown in Figure 9. Student user authentication means that during the Japanese online exam, the examinee can log in to the system to take the exam only after he/she has passed face recognition or ID card recognition [23]. Identity authentication is very important in the process of Japanese online examination.…”

Section: Experiments and Analysismentioning

confidence: 99%

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Dengqing

Zhangwei

2022

Wireless Communications and Mobile Computing

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In order to solve the problem of online inspection of students’ theoretical knowledge of Japanese, this paper further optimizes and adjusts the design of the online Japanese examination system and presents an online Japanese examination system based on genetic algorithm. Taking the Japanese test as the research object, on the basis of comprehensively analyzing the problems of slow test paper composition, low success rate, and low quality of traditional online test systems, an intelligent test composition model based on genetic algorithm is proposed, and the implementation process of genetic algorithm and the key steps are described in detail. The results show that the online Japanese examination system based on genetic algorithm can meet the needs of test paper generation in more complex situations. After a long time of operation and continuous improvement, the online Japanese examination system has obtained the adaptability of the best solution. The value of the fitness is 99.666667; when the fitness is at this value, the error of the question type score of the test paper is 0, the average difficulty error on the test paper is 0, and the error of the section test point distribution is 0.666667. This fully illustrates the stability and effectiveness of the Japanese online examination system, which can meet the needs of daily Japanese majors and improve the efficiency of Japanese teaching.

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Section: Experiments and Analysismentioning

confidence: 99%

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Dengqing

Zhangwei

2022

Wireless Communications and Mobile Computing

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“…In [18], artificial bee colony (ABC) based priority based load shed is solved in islanded MG with RES for sudden load increment and line contingencies. In [19], a multiple-deme parallel genetic algorithm (MDPGA) is introduced for load balance when there is a low voltage stability margin due to either line contingencies and/or generator failures. In [20][21][22], based on the coordination of the load importance factor (LIF), the reciprocal phase angle sensitivity (RPAS), and the voltage electrical distance (VED) to rank the load buses, the analytical hierarchy process (AHP) algorithm-based approach to load shedding for restoring the frequency under generation shortage is used.…”

Section: Introductionmentioning

confidence: 99%

Pelican Optimization Algorithm for Optimal Demand Response in Islanded Active Distribution Network Considering Controllable Loads

2022

IJIES

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One of the challenging tasks in an active distribution network (AND) embedded with intermittent renewable energy sources (RES) under islanding conditions is the maintenance of frequency and voltage profiles within tolerable limits. Failing to maintain these operational requirements may lead to voltage collapse or complete blackout of the network. In order to avoid this scenario, ADNs may function with contemporary load shedding schemes but these schemes may result in an inadvertent and excessive amount of load shedding, thereby consequently causing unsatisfactory and low reliability at the consumer level. Thus, this paper used Pelican optimization algorithm (POA) approach for minimising the amount of load to be shed by determining the optimal amount of load to be shed within the consumers' specified limits. Simulations are performed on IEEE 33-bus by assuming different kinds of renewable and distribution generation (DG) units. The computational efficiency of POA is compared with literature works and its performance is also characterised based on 25-indipendent runs of each case. The results obtained by POA are observed to be superior in terms of global optima and less run time. Also, the ADN is observed as satisfactory operation with fewer distribution losses, an improved voltage profile, and enhanced stability margins by imposing optimal load controls to the consumer.

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“…Step 3: Use the crossover operator in the genetic operator [28] and the variation operator [28] based on the historical record matrix to generate the offspring Y. The mixing produces a new population Z.…”

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confidence: 99%

“…max − 𝑓 𝑞 min , 𝑞 = 1, … , 𝑚 (28). where 𝑁 * is the number of non-dominated solutions and 𝑓 ̅ 𝑞 𝑖 is the normalized value of the target 𝑓 𝑞 𝑖 for any individual.…”

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confidence: 99%

A virtual model knowledge updating method driven by data

Luo

Sheng

et al. 2023

Int J Adv Manuf Technol

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The initial construction of the unit-level virtual model in the discrete production line lacks the understanding of physical entities and the actual operating environment, which makes it difficult for the virtual model knowledge to correctly drive the behavior of physical entities. In order to solve the above problems, a virtual model knowledge updating method driven by data is studied. Firstly, the knowledge in the virtual model is divided into basic functional units according to functions, and the knowledge of each functional unit is encapsulated into knowledge components such as forward kinematics, motion control, material generation, etc., and the knowledge component base is constructed. Secondly, this method establishes the evaluation index of effectiveness, usability, and reliability of knowledge components, and can screen out appropriate groups of knowledge component combinations from the knowledge component base. Then, based on the measurement value, it is used to update the trigger judgment and select a group of knowledge components with the smallest difference between the simulation output of virtual model and the real data of physical entities from multiple groups of knowledge combinations, so as to realize the iterative update of the model. Finally, the feasibility and effectiveness of the method are verified by examples.

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Multiple-deme parallel genetic algorithm based on modular neural network for effective load shedding

Cited by 4 publications

References 52 publications

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Design and Implementation of Online Japanese Examination System Based on Genetic Algorithm

Pelican Optimization Algorithm for Optimal Demand Response in Islanded Active Distribution Network Considering Controllable Loads

A virtual model knowledge updating method driven by data

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