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Shuo Wang, Liaojun Zhang and Guojiang Yin
Research on the vibration response prediction and safety early warning is of great significance to the operation and management of pumping station engineering. In the current research, a hybrid prediction method was proposed to predict vibration response...
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Hossam Fraihat, Amneh A. Almbaideen, Abdullah Al-Odienat, Bassam Al-Naami, Roberto De Fazio and Paolo Visconti
Solar energy is one of the most important renewable energies, with many advantages over other sources. Many parameters affect the electricity generation from solar plants. This paper aims to study the influence of these parameters on predicting solar rad...
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Yog Aryal
Accurately predicting ambient dust plays a crucial role in air quality management and hazard mitigation. Dust emission is a complex, non-linear response to several climatic variables. This study explores the accuracy of Artificial Intelligence (AI) model...
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Rafael Akira Akisue, Matheus Lopes Harth, Antonio Carlos Luperni Horta and Ruy de Sousa Junior
Due to low oxygen solubility and mechanical stirring limitations of a bioreactor, ensuring an adequate oxygen supply during a recombinant Escherichia coli cultivation is a major challenge in process control. Under the light of this fact, a fuzzy dissolve...
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Mohammad Sadegh Es-haghi, Mohsen Abbaspour, Hamidreza Abbasianjahromi and Stefano Mariani
The seismic bearing capacity of a shallow strip footing above a void displays a complex dependence on several characteristics, linked to geometric problems and to the soil properties. Hence, setting analytical models to estimate such bearing capacity is ...
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Sina F. Ardabili, Amir Mosavi, Pedram Ghamisi, Filip Ferdinand, Annamaria R. Varkonyi-Koczy, Uwe Reuter, Timon Rabczuk and Peter M. Atkinson
Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and s...
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Hoang-Long Nguyen, Binh Thai Pham, Le Hoang Son, Nguyen Trung Thang, Hai-Bang Ly, Tien-Thinh Le, Lanh Si Ho, Thanh-Hai Le and Dieu Tien Bui
The International Roughness Index (IRI) is the one of the most important roughness indexes to quantify road surface roughness. In this paper, we propose a new hybrid approach between adaptive network based fuzzy inference system (ANFIS) and various meta-...
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Hoang-Long Nguyen, Thanh-Hai Le, Cao-Thang Pham, Tien-Thinh Le, Lanh Si Ho, Vuong Minh Le, Binh Thai Pham and Hai-Bang Ly
The main objective of this study is to develop and compare hybrid Artificial Intelligence (AI) approaches, namely Adaptive Network-based Fuzzy Inference System (ANFIS) optimized by Genetic Algorithm (GAANFIS) and Particle Swarm Optimization (PSOANFIS) an...
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Ângelo de Carvalho Paulino, Lamartine Nogueira Frutuoso Guimarães, Dr., Elcio Hideiti Shiguemori, Dr.
Pág. 162 - 195
Nowadays, there is a remarkable world trend in employing UAVs and drones for diverse applications. The main reasons are that they may cost fractions of manned aircraft and avoid the exposure of human lives to risks. Nevertheless, they depend on positioni...
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Salaheddin Hosseinzadeh, Hadi Larijani, Krystyna Curtis and Andrew Wixted
This article proposes an adaptive-network-based fuzzy inference system (ANFIS) model for accurate estimation of signal propagation using LoRaWAN. By using ANFIS, the basic knowledge of propagation is embedded into the proposed model. This reduces the tra...
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