PSO-based Power-Driven X-Routing Algorithm in semiconductor design for predictive intelligence of IoT applications

Liu, Genggeng; Zhu, Yuhan; Xu, Saijuan; Chen, Yeh-Cheng; Tang, Hao

doi:10.1016/j.asoc.2021.108114

Cited by 29 publications

(16 citation statements)

References 36 publications

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“…From the SMS findings, a framework for systematically analyzing and comparing RPA works is derived. e discovered thematic clusters suggest further investigations to develop a more elaborated structural research approach for RPA [22][23][24].…”

Section: Hyperautomationmentioning

confidence: 84%

Automatic Generation of Real-Time Animation Game Learning Levels Based on Artificial Intelligence Assistant

Zhang

2022

Scientific Programming

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With the development of computer animation games, now many animation games use the automatic generation of animation game levels method to generate animation game content. Using the automatic generation levels of the animation game method can quickly generate many different levels, saving labor costs in manual production. And with the combination of other fields, more accurate results can be obtained. In this paper, the goal is to automatically generate the level of the animation game. This research proposed animation game objects and victory conditions to derive the concept of the clearance path and uses artificial intelligence genetic algorithms to obtain the clearance path that best meets the needs of the developer to recombine new levels. In addition, since the generated levels are regenerated from the clearance path, there are still too many blank areas. In order to make full use of these blank areas, this research provides a level complete system. The system has formulated its placement rules for existing animation game objects. These rules fill in these blank areas and produce a more complete level. The contributions of this search proved that the genetic algorithm can converge quickly due to the correction effect in the mutation. In the complete system, it has successfully achieved a complete and playable level. In the system running time, this research adjusted the method of selecting elites and the use of permutations and combinations to mate, so that the system’s operation can be stabilized on an average value.

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Section: Hyperautomationmentioning

confidence: 84%

Automatic Generation of Real-Time Animation Game Learning Levels Based on Artificial Intelligence Assistant

Zhang

2022

Scientific Programming

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“…The intention of students’ use behavior was also set as a variable. It was concluded that perceived usefulness, course content, brand image, function, and attractiveness have a positive effect on college students’ acceptance of online courses, and perceived ease of use has a positive effect on college students’ acceptance of online courses ( Liu G. et al, 2020 ; Liu N. et al, 2020 ; Liu et al, 2021 , 2022a , b ).…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

Research on the state of blended learning among college students – A mixed-method approach

Deng¹,

Jiao²,

2022

Front. Psychol.

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In the wake of the COVID-19 pandemic in 2019, China’s education leaders began to focus on and promote blended learning. The process is still in its infancy in Chinese colleges and universities, and its development remains a problem to be solved. By combining technology acceptance and student participation, this article proposes an analysis model for assessing the factors influencing blended learning. A questionnaire was designed and distributed, and 796 valid responses were collected. The mean and variance were used to examine the status of students’ technology acceptance and satisfaction with blended learning. The t-test method was employed to analyze the gender differences between students in regard to the topic. The results show that: (1) students majoring in computer science view the factors as having a high level of influence in blended learning. (2) There are major variances regarding the perception of service quality between male and female computer science major students. There is no significant difference between them in terms of perceived usefulness, perceived ease of use, or computer self-efficacy. (3) There are considerable disparities in the skill involvement and participation of computer science major college students. The results show that the technology acceptance and participation of students determine the effect of blended learning. Based on these findings, this article provides theoretical and practical suggestions for the implementation of blended learning to improve its effect.

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“…It has been widely used in various fields such as combinatorial optimization [10][11][12][13], image matching and enhancement [14,15], and data mining [16,17]. Besides, the PSO algorithm has been successfully applied to some routing problems with good results [18][19][20]. Therefore, the PSO technique is one of the effective methods to break the bottleneck of traditional routing algorithms.…”

Section: Introductionmentioning

confidence: 99%

SLDPSO-TA: Track Assignment Based on Social Learning Discrete Particle Swarm Optimization

Liu

Jing

Zhou

et al. 2023

Preprint

Self Cite

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In the modern Very Large Scale Integration (VLSI) circuit design, the short-circuit problem is one of the key factors affecting routability. Due to the increased circuit size and net density, the short-circuit problem grows significantly in detailed routing. Furthermore, global routing ignores many problems in detailed routing, making for an increased mismatch between global routing and detailed routing. As a crucial intermediate phase between global routing and detailed routing, track assignment is an excellent phase to pre-process the short-circuit problem. However, existing track assignment algorithms face the problem of falling into local optimality. As one of the typical representatives of the swarm intelligence techniques, Particle Swarm Optimization (PSO) is a powerful tool to solve large-scale discrete problems. Therefore, we propose an effective Track Assignment Algorithm Based on Social Learning Discrete Particle Swarm Optimization (SLDPSO-TA). First, the proposed algorithm considers local nets to better guide detailed routing and an effective encoding method is designed to adapt the evolutionary algorithms better. Second, the social learning mode based on example pool mechanism is presented to improve the algorithm performance. Finally, a negotiation-based refining strategy is utilized to further reduce the overlap. Experimental results show that SLDPSO-TA can obtain the best overlap cost optimization among similar works, and reduce the congestion in key routing areas.

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PSO-based Power-Driven X-Routing Algorithm in semiconductor design for predictive intelligence of IoT applications

Cited by 29 publications

References 36 publications

Automatic Generation of Real-Time Animation Game Learning Levels Based on Artificial Intelligence Assistant

Automatic Generation of Real-Time Animation Game Learning Levels Based on Artificial Intelligence Assistant

Research on the state of blended learning among college students – A mixed-method approach

SLDPSO-TA: Track Assignment Based on Social Learning Discrete Particle Swarm Optimization

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