FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3211323786> ?p ?o ?g. }

• W3211323786 endingPage "104010" @default.
• W3211323786 startingPage "104010" @default.
• W3211323786 abstract "Evacuation is critical for safety management due to the highly overcrowded passengers in the metro stations. A simulation-based approach integrating Random Forest (RF) and Non-dominated Sorting Genetic Algorithm III (NSGA-III) is proposed to perform the evacuation evaluation and optimization at metro stations. A 3D model of the metro station is built to simulate the dynamic process of passenger evacuation in metro stations. A framework consisting of 9 influential factors and 3 objectives is developed to model the input-output relationship in passenger evacuation. An RF-based meta-model is used to construct the relationship between influential factors and objectives. At last, NSGA-III is applied to seeking the optimal solutions for the station renovation in order to achieve a safe evacuation. A station model simulating a real metro station in Singapore is constructed to test the effectiveness and applicability of the proposed approach. It is found that (1) A safe evacuation could be achieved for the station, but along with the increasing passenger volume and panic level, the requirement of evacuation objectives, the evacuation time and density, may not be met. Especially under the high passenger volume conditions, the passenger density could reach up to 6.2 unit/m2 (extremely dangerous); (2) An average improvement degree, 7.5%, can be achieved for the optimization of 20 test cases, and a maximum improvement degree, 22.5%, can be achieved for the evacuation optimization at metro stations; (3) It could be difficult to keep both of the evacuation time and density within the standards if one major exit is closed, even after the optimization. But a larger average improvement degree, 10.8%, can be achieved by the proposed optimization approach, which indicates the optimal solutions still could reduce the risk to a great extent. The novelty of this research lies in that (a) An RF algorithm is incorporated to build the meta-model that can properly represent the relationship between influential factors and objectives, despite the complexity and even conflicting between them; (b) Optimal measures for the evacuation improvement are provided from the MOO perspective by integrating NSGA-III. This hybrid approach can be used as a decision tool to assist regulatory authorities in developing effective emergency evacuation evaluation and optimization plans with adequate consideration of the complexity and multi-objective nature under evacuation events." @default.
• W3211323786 created "2021-11-08" @default.
• W3211323786 creator A5024092132 @default.
• W3211323786 creator A5056869509 @default.
• W3211323786 date "2022-01-01" @default.
• W3211323786 modified "2023-10-08" @default.
• W3211323786 title "Simulation-based passenger evacuation optimization in metro stations considering multi-objectives" @default.
• W3211323786 cites W1904463290 @default.
• W3211323786 cites W1984752243 @default.
• W3211323786 cites W1991635657 @default.
• W3211323786 cites W1995225412 @default.
• W3211323786 cites W1995899784 @default.
• W3211323786 cites W2001036928 @default.
• W3211323786 cites W2006840735 @default.
• W3211323786 cites W2017937504 @default.
• W3211323786 cites W2018567788 @default.
• W3211323786 cites W2029871071 @default.
• W3211323786 cites W2038913727 @default.
• W3211323786 cites W2039978868 @default.
• W3211323786 cites W2049231397 @default.
• W3211323786 cites W2074089239 @default.
• W3211323786 cites W2075421046 @default.
• W3211323786 cites W2081447208 @default.
• W3211323786 cites W2086276449 @default.
• W3211323786 cites W2184314524 @default.
• W3211323786 cites W2278556058 @default.
• W3211323786 cites W2511583611 @default.
• W3211323786 cites W2517866598 @default.
• W3211323786 cites W2547948715 @default.
• W3211323786 cites W2554758365 @default.
• W3211323786 cites W2560339071 @default.
• W3211323786 cites W2563849660 @default.
• W3211323786 cites W2577113988 @default.
• W3211323786 cites W2596084689 @default.
• W3211323786 cites W2602476701 @default.
• W3211323786 cites W2604108110 @default.
• W3211323786 cites W2605281298 @default.
• W3211323786 cites W2606798262 @default.
• W3211323786 cites W2608878010 @default.
• W3211323786 cites W2743805607 @default.
• W3211323786 cites W2790985907 @default.
• W3211323786 cites W2791143113 @default.
• W3211323786 cites W2792571375 @default.
• W3211323786 cites W2799827219 @default.
• W3211323786 cites W2804307570 @default.
• W3211323786 cites W2809233446 @default.
• W3211323786 cites W2892755442 @default.
• W3211323786 cites W2900068535 @default.
• W3211323786 cites W2905898036 @default.
• W3211323786 cites W2937887623 @default.
• W3211323786 cites W2956832872 @default.
• W3211323786 cites W2959465742 @default.
• W3211323786 cites W2968834107 @default.
• W3211323786 cites W2971942705 @default.
• W3211323786 cites W2980384159 @default.
• W3211323786 cites W2985755248 @default.
• W3211323786 cites W2996705655 @default.
• W3211323786 cites W2998957534 @default.
• W3211323786 cites W3008441192 @default.
• W3211323786 cites W3010074491 @default.
• W3211323786 cites W3022766137 @default.
• W3211323786 cites W3028812916 @default.
• W3211323786 cites W3033049120 @default.
• W3211323786 cites W3035353528 @default.
• W3211323786 cites W3037875075 @default.
• W3211323786 cites W3085722926 @default.
• W3211323786 cites W3087727440 @default.
• W3211323786 cites W3089187531 @default.
• W3211323786 cites W3094047202 @default.
• W3211323786 cites W3112786882 @default.
• W3211323786 cites W3128641904 @default.
• W3211323786 cites W3128714328 @default.
• W3211323786 cites W3131879247 @default.
• W3211323786 cites W3183217260 @default.
• W3211323786 doi "https://doi.org/10.1016/j.autcon.2021.104010" @default.
• W3211323786 hasPublicationYear "2022" @default.
• W3211323786 type Work @default.
• W3211323786 sameAs 3211323786 @default.
• W3211323786 citedByCount "20" @default.
• W3211323786 countsByYear W32113237862022 @default.
• W3211323786 countsByYear W32113237862023 @default.
• W3211323786 crossrefType "journal-article" @default.
• W3211323786 hasAuthorship W3211323786A5024092132 @default.
• W3211323786 hasAuthorship W3211323786A5056869509 @default.
• W3211323786 hasConcept C111696304 @default.
• W3211323786 hasConcept C119857082 @default.
• W3211323786 hasConcept C121332964 @default.
• W3211323786 hasConcept C127413603 @default.
• W3211323786 hasConcept C199360897 @default.
• W3211323786 hasConcept C20556612 @default.
• W3211323786 hasConcept C22212356 @default.
• W3211323786 hasConcept C2994559806 @default.
• W3211323786 hasConcept C41008148 @default.
• W3211323786 hasConcept C44154836 @default.
• W3211323786 hasConcept C62520636 @default.
• W3211323786 hasConcept C8880873 @default.
• W3211323786 hasConceptScore W3211323786C111696304 @default.
• W3211323786 hasConceptScore W3211323786C119857082 @default.

• next