Optimization of ANFIS Network Using Particle Swarm Optimization Modeling of Scour around Submerged Pipes
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RESEARCH ARTICLE
Optimization of ANFIS Network Using Particle Swarm Optimization Modeling of Scour around Submerged Pipes Rahim Gerami Moghadam 1 & Saeid Shabanlou 1 & Fariborz Yosefvand 1 Received: 6 November 2019 / Accepted: 6 June 2020 # Harbin Engineering University and Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In general, submerged pipes passing over the sedimentary bed of seas are installed for transmitting oil and gas to coastal regions. The stability of submerged pipes can be threatened with waves and coastal flows occurring at coastal regions. In this study, for the first time, the adaptive neuro-fuzzy inference system (ANFIS) is optimized using the particle swarm optimization (PSO) algorithm, and a meta-heuristic artificial intelligence model is developed for simulating the scour pattern around submerged pipes located in sedimentary beds. Afterward, six ANFIS-PSO models are developed by means of parameters affecting the scour depth. Then, the superior model is detected through sensitivity analysis. This model has the function of all input parameters. The calculated correlation coefficient and scatter index for this model are 0.993 and 0.047, respectively. The ratio of the pipe distance from the sedimentary bed to the submerged pipe diameter is introduced as the most effective input parameter. PSO significantly improves the performance of the ANFIS model. Approximately 36% of the scour depths simulated using the ANFIS model have an error less than 5%, whereas the value for ANFIS-PSO is roughly 72%. Keywords Adaptive neuro-fuzzy inference system (ANFIS) . Meta-heuristic model . Particle swarm optimization (PSO) . Scour around submerged pipes . Coastal regions
1 Introduction Nowadays, given the operation of undersea oil and gas reservoirs located in coastal regions, the transport of these fossil fuels to lands requires the use of pipelines. Pipelines are generally placed near erodible sea beds, and scour formation can possibly occur due to the existence of flows and waves. As an
Article Highlights • The adaptive neuro-fuzzy inference system (ANFIS) was optimized using the particle swarm optimization (PSO), and ANFIS-PSO model was defined. • The scour depth around submerged pipes located in sedimentary bed was estimated using the ANFIS-PSO model. • The most important parameters affecting the scout depth were identified. • The performance of ANFIS-PSO model was compared with the ANFIS network, with a superiority of ANFIS-PSO. * Saeid Shabanlou [email protected] 1
Department of Water Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah 6718997551, Iran
erodible bed is scoured, the stability of pipelines is threatened with the risk of large deformations and failure. Thus, given the importance of this issue, experimental, analytical, and numerical studies have been carried out on the scour pattern in the vicinity of submerged pipelines. Fredsoe et al. (1988) experimentally investigated the twodimensional scour pattern in the vicinity of submerged pipes locate
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