{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T16:09:17Z","timestamp":1782317357821,"version":"3.54.5"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T00:00:00Z","timestamp":1697500800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T00:00:00Z","timestamp":1697500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Wireless Netw"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s11276-023-03535-x","type":"journal-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T07:02:10Z","timestamp":1697526130000},"page":"6809-6820","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Particle Filtering SLAM algorithm for urban pipe leakage detection and localization"],"prefix":"10.1007","volume":"30","author":[{"given":"Hongfei","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaowei","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liyue","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Degang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,17]]},"reference":[{"issue":"15","key":"3535_CR1","doi-asserted-by":"publisher","first-page":"8085","DOI":"10.1016\/j.jfranklin.2021.08.012","volume":"358","author":"N He","year":"2021","unstructured":"He, N., Qian, C., Li, R., & Zhang, M. (2021). An improved pipeline leak detection and localization method based on compressed sensing and event-triggered particle filter. Journal of the Franklin Institute, 358(15), 8085\u20138108.","journal-title":"Journal of the Franklin Institute"},{"issue":"3","key":"3535_CR2","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1007\/s11370-022-00410-0","volume":"15","author":"S Kazeminasab","year":"2022","unstructured":"Kazeminasab, S., & Banks, M. K. (2022). Towards long-distance inspection for in-pipe robots in water distribution systems with smart motion facilitated by particle filter and multi-phase motion controller. Intelligent Service Robotics, 15(3), 259\u2013273.","journal-title":"Intelligent Service Robotics"},{"key":"3535_CR3","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1016\/j.neucom.2020.04.105","volume":"403","author":"C Wang","year":"2020","unstructured":"Wang, C., Han, F., Zhang, Y., & Lu, J. (2020). An SAE-based resampling SVM ensemble learning paradigm for pipeline leakage detection. Neurocomputing, 403, 237\u2013246.","journal-title":"Neurocomputing"},{"issue":"04","key":"3535_CR4","first-page":"787","volume":"28","author":"LL He","year":"2021","unstructured":"He, L. L., Chen, Y. X., & He, N. (2021). Research on pipeline leak detection and location method based on particle filter. Control Engineering China, 28(04), 787\u2013798.","journal-title":"Control Engineering China"},{"key":"3535_CR5","doi-asserted-by":"publisher","first-page":"140173","DOI":"10.1109\/ACCESS.2021.3115981","volume":"9","author":"JM Aitken","year":"2021","unstructured":"Aitken, J. M., Evans, M. H., Worley, R., Edwards, S., Zhang, R., Dodd, T., Mihaylova, L., & Anderson, S. R. (2021). Simultaneous localization and mapping for inspection robots in water and sewer pipe networks: A review. IEEE Access, 9, 140173\u2013140198.","journal-title":"IEEE Access"},{"issue":"6","key":"3535_CR6","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1080\/1573062X.2020.1797832","volume":"17","author":"M Shekofteh","year":"2020","unstructured":"Shekofteh, M., Jalili Ghazizadeh, M., & Yazdi, J. (2020). A methodology for leak detection in water distribution networks using graph theory and artificial neural network. Urban Water Journal, 17(6), 525\u2013533.","journal-title":"Urban Water Journal"},{"issue":"03","key":"3535_CR7","doi-asserted-by":"publisher","first-page":"196","DOI":"10.36548\/jucct.2021.3.004","volume":"3","author":"RR Sharma","year":"2021","unstructured":"Sharma, R. R. (2021). Gas leakage detection in pipeline by svm classifier with automatic eddy current based defect recognition method. Journal of Ubiquitous Computing and Communication Technologies (UCCT), 3(03), 196\u2013212.","journal-title":"Journal of Ubiquitous Computing and Communication Technologies (UCCT)"},{"issue":"02","key":"3535_CR8","doi-asserted-by":"publisher","first-page":"2259001","DOI":"10.1142\/S0218001422590017","volume":"36","author":"Z Chi","year":"2022","unstructured":"Chi, Z., Jiang, J., Diao, X., Chen, Q., Ni, L., Wang, Z., & Shen, G. (2022). Novel leakage detection method by improved adaptive filtering and pattern recognition based on acoustic waves. International Journal of Pattern Recognition and Artificial Intelligence, 36(02), 2259001.","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"},{"key":"3535_CR9","first-page":"1","volume":"71","author":"X Han","year":"2022","unstructured":"Han, X., Cao, W., Cui, X., Gao, Y., & Liu, F. (2022). Plastic pipeline leak localization based on wavelet packet decomposition and higher order cumulants. IEEE Transactions on Instrumentation and Measurement, 71, 1\u201311.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"3535_CR10","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1016\/j.psep.2022.01.021","volume":"159","author":"AZ Selvaggio","year":"2022","unstructured":"Selvaggio, A. Z., Sousa, F. M. M., da Silva, F. V., & Vianna, S. S. (2022). Application of long short-term memory recurrent neural networks for localisation of leak source using 3D computational fluid dynamics. Process Safety and Environmental Protection, 159, 757\u2013767.","journal-title":"Process Safety and Environmental Protection"},{"issue":"188","key":"3535_CR11","doi-asserted-by":"publisher","first-page":"20210849","DOI":"10.1098\/rsif.2021.0849","volume":"19","author":"J Yuk","year":"2022","unstructured":"Yuk, J., Chakraborty, A., Cheng, S., Chung, C. I., Jorgensen, A., Basu, S., Chamorro, L. P., & Jung, S. (2022). On the design of particle filters inspired by animal noses. Journal of the Royal Society Interface, 19(188), 20210849.","journal-title":"Journal of the Royal Society Interface"},{"issue":"12","key":"3535_CR12","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/ac298e","volume":"32","author":"J Zhang","year":"2021","unstructured":"Zhang, J., Lian, Z., Zhou, Z., Zhang, J., Xiong, M., & Liu, J. (2021). Numerical and experimental study on leakage detection for buried gas pipelines based on distributed optical fiber acoustic wave. Measurement Science and Technology, 32(12), 125209.","journal-title":"Measurement Science and Technology"},{"issue":"2","key":"3535_CR13","doi-asserted-by":"publisher","first-page":"4969","DOI":"10.1109\/LRA.2022.3154482","volume":"7","author":"MM Dos Santos","year":"2022","unstructured":"Dos Santos, M. M., De Giacomo, G. G., Drews-Jr, P. L., & Botelho, S. S. (2022). Cross-view and cross-domain underwater localization based on optical aerial and acoustic underwater images. IEEE Robotics and Automation Letters, 7(2), 4969\u20134974.","journal-title":"IEEE Robotics and Automation Letters"},{"issue":"3","key":"3535_CR14","doi-asserted-by":"publisher","DOI":"10.1115\/1.4053141","volume":"19","author":"N He","year":"2022","unstructured":"He, N., Qian, C., & He, L. (2022). Short-term prediction of remaining life for lithium-ion battery based on adaptive hybrid model with long short-term memory neural network and optimized particle filter. Journal of Electrochemical Energy Conversion and Storage, 19(3), 031004.","journal-title":"Journal of Electrochemical Energy Conversion and Storage"},{"issue":"7","key":"3535_CR15","doi-asserted-by":"publisher","first-page":"3282","DOI":"10.2166\/ws.2021.101","volume":"21","author":"Z Hu","year":"2021","unstructured":"Hu, Z., Chen, B., Chen, W., Tan, D., & Shen, D. (2021). Review of model-based and data-driven approaches for leak detection and location in water distribution systems. Water Supply, 21(7), 3282\u20133306.","journal-title":"Water Supply"},{"issue":"2","key":"3535_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpse.2022.02.001","volume":"2","author":"H Fu","year":"2022","unstructured":"Fu, H., Ling, K., & Pu, H. (2022). Identifying two-point leakages in parallel pipelines based on flow parameter analysis. Journal of Pipeline Science and Engineering, 2(2), 100052.","journal-title":"Journal of Pipeline Science and Engineering"},{"issue":"2","key":"3535_CR17","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1109\/JOE.2022.3223733","volume":"48","author":"J Zhou","year":"2023","unstructured":"Zhou, J., Pang, L., & Zhang, W. (2023). Underwater image enhancement method by multi-interval histogram equalization. IEEE Journal of Oceanic Engineering, 48(2), 474\u2013488.","journal-title":"IEEE Journal of Oceanic Engineering"},{"issue":"9","key":"3535_CR18","doi-asserted-by":"publisher","first-page":"05022005","DOI":"10.1061\/(ASCE)WR.1943-5452.0001574","volume":"148","author":"Z Li","year":"2022","unstructured":"Li, Z., Wang, J., Yan, H., Li, S., Tao, T., & Xin, K. (2022). Fast detection and localization of multiple leaks in water distribution network jointly driven by simulation and machine learning. Journal of Water Resources Planning and Management, 148(9), 05022005.","journal-title":"Journal of Water Resources Planning and Management"},{"issue":"7","key":"3535_CR19","doi-asserted-by":"publisher","first-page":"7107","DOI":"10.1109\/TCYB.2020.3035518","volume":"52","author":"H Zhang","year":"2020","unstructured":"Zhang, H., Hu, X., Ma, D., Wang, R., & Xie, X. (2020). Insufficient data generative model for pipeline network leak detection using generative adversarial networks. IEEE Transactions on Cybernetics, 52(7), 7107\u20137120.","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"9","key":"3535_CR20","doi-asserted-by":"publisher","first-page":"840","DOI":"10.3390\/mi11090840","volume":"11","author":"L Guan","year":"2020","unstructured":"Guan, L., Cong, X., Zhang, Q., Liu, F., Gao, Y., An, W., & Noureldin, A. (2020). A comprehensive review of micro-inertial measurement unit based intelligent PIG multi-sensor fusion technologies for small-diameter pipeline surveying. Micromachines, 11(9), 840.","journal-title":"Micromachines"},{"issue":"4","key":"3535_CR21","doi-asserted-by":"publisher","first-page":"04023026","DOI":"10.1061\/JPSEA2.PSENG-1439","volume":"14","author":"U Rajasekaran","year":"2023","unstructured":"Rajasekaran, U., & Kothandaraman, M. (2023). comparative analysis of machine learning and deep learning based water pipeline leak detection using EDFL sensor. Journal of Pipeline Systems Engineering and Practice, 14(4), 04023026.","journal-title":"Journal of Pipeline Systems Engineering and Practice"},{"key":"3535_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2022.3206833","volume":"71","author":"TB Quy","year":"2022","unstructured":"Quy, T. B., & Kim, J. M. (2022). Pipeline leak detection using acoustic emission and state estimate in feature space. IEEE Transactions on Instrumentation and Measurement, 71, 1\u20139.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"3535_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.105952","volume":"121","author":"J Zhou","year":"2023","unstructured":"Zhou, J., Zhang, D., & Zhang, W. (2023). Cross-view enhancement network for underwater images. Engineering Applications of Artificial Intelligence, 121, 105952.","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"10","key":"3535_CR24","doi-asserted-by":"publisher","first-page":"259","DOI":"10.3390\/lubricants10100259","volume":"10","author":"CJ Kamp","year":"2022","unstructured":"Kamp, C. J., & Bagi, S. D. (2022). Implications of the use of biodiesel on the longevity and operation of particle filters. Lubricants, 10(10), 259.","journal-title":"Lubricants"},{"issue":"4","key":"3535_CR25","doi-asserted-by":"publisher","first-page":"782","DOI":"10.2166\/hydro.2021.164","volume":"23","author":"EG Mohammed","year":"2021","unstructured":"Mohammed, E. G., Zeleke, E. B., & Abebe, S. L. (2021). Water leakage detection and localization using hydraulic modeling and classification. Journal of Hydroinformatics, 23(4), 782\u2013794.","journal-title":"Journal of Hydroinformatics"},{"issue":"11","key":"3535_CR26","doi-asserted-by":"publisher","first-page":"11723","DOI":"10.1109\/TIE.2021.3127016","volume":"69","author":"X Hu","year":"2021","unstructured":"Hu, X., Zhang, H., Ma, D., Wang, R., & Tu, P. (2021). Small leak location for intelligent pipeline system via action-dependent heuristic dynamic programming. IEEE Transactions on Industrial Electronics, 69(11), 11723\u201311732.","journal-title":"IEEE Transactions on Industrial Electronics"},{"issue":"1","key":"3535_CR27","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1109\/TVLSI.2021.3100252","volume":"30","author":"P Shukla","year":"2021","unstructured":"Shukla, P., Muralidhar, A., Iliev, N., Tulabandhula, T., Fuller, S. B., & Trivedi, A. R. (2021). Ultralow-power localization of insect-scale drones: Interplay of probabilistic filtering and compute-in-memory. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 30(1), 68\u201380.","journal-title":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems"}],"container-title":["Wireless Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-023-03535-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11276-023-03535-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-023-03535-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,13]],"date-time":"2024-11-13T13:21:29Z","timestamp":1731504089000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11276-023-03535-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,17]]},"references-count":27,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["3535"],"URL":"https:\/\/doi.org\/10.1007\/s11276-023-03535-x","relation":{},"ISSN":["1022-0038","1572-8196"],"issn-type":[{"value":"1022-0038","type":"print"},{"value":"1572-8196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,17]]},"assertion":[{"value":"26 September 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 October 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Authors do not have any conflicts.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}