Ssenger travel time and the total variety of operating trains. Meanwhile, a answer algorithm primarily based on a genetic algorithm is proposed to resolve the model. On the basis of preceding research, this paper mostly focuses on schedule adjustment, optimization of a stop strategy and frequency under the overtaking condition, which can maximize the line capacity. A case of Jiangjin Line in Chongqing is used to show the reasonability and effectiveness in the proposed model and algorithm. The results show that total travel time in E/L mode together with the overtaking PF-07321332 Epigenetics condition is drastically decreased compared with AS mode and E/L mode with no the overtaking situation. Although the number of trains inside the optimal remedy is greater than other modes, the E/L mode with the overtaking condition continues to be superior than other modes on the complete. Rising the station cease time can boost the superiority of E/L mode over AS mode. The analysis final results of this paper can give a reference for the optimization analysis of skip-stop operation under overtaking conditions and offer proof for urban rail transit operators and planners. There are still some aspects that could be extended in future perform. Firstly, this paper assumes that passengers take the very first train to arrive in the station, whether or not it is the express train or neighborhood train. In reality, the passenger’s option of train is actually a probability trouble, as a result the passenger route option behaviorAppl. Sci. 2021, 11,16 ofconsidering the train congestion really should be viewed as in future studies. In addition, genetic algorithms have the characteristics of acquiring partial optimal options rather than international optimal options. The optimization dilemma of the genetic algorithm for solving skip-stop operation optimization models is also a vital study tendency.Author Contributions: Each authors took Clevidipine-d7 Epigenetics element inside the discussion in the operate described within this paper. Writing–original draft preparation, J.X.; methodology, J.X.; writing–review and editing, Q.L.; information curation, X.H., L.W. All authors have study and agreed for the published version of the manuscript. Funding: This study received no external funding. Institutional Overview Board Statement: Not applicable. Informed Consent Statement: Not applicable. Information Availability Statement: The information presented in this study are obtainable on request from the corresponding author. Acknowledgments: The authors thank Songsong Li and Kuo Han, for their constructive comments and recommendations in this study. Conflicts of Interest: The authors declare no conflict of interest.
applied sciencesArticleWiFi Positioning in 3GPP Indoor Workplace with Modified Particle Swarm OptimizationSung Hyun Oh and Jeong Gon Kim Division of Electronic Engineering, Korea Polytechnic University, Siheung-si 15297, Korea; [email protected] Correspondence: [email protected]; Tel.: +82-10-9530-Citation: Oh, S.H.; Kim, J.G. WiFi Positioning in 3GPP Indoor Office with Modified Particle Swarm Optimization. Appl. Sci. 2021, 11, 9522. https://doi.org/10.3390/ app11209522 Academic Editor: Jaehyuk Choi Received: 1 September 2021 Accepted: 10 October 2021 Published: 13 OctoberAbstract: With the start out on the Fourth Industrial Revolution, Net of Items (IoT), artificial intelligence (AI), and massive data technologies are attracting international focus. AI can reach quickly computational speed, and huge information tends to make it attainable to shop and use vast amounts of information. Furthermore, smartphones, which are IoT devices, are owned by most p.
