Artificial intelligence applications for friction stir welding: A review
Advances in artificial intelligence (AI) techniques that can be used for different purposes
have enabled it to be used in many different industrial applications. These are mainly used …
have enabled it to be used in many different industrial applications. These are mainly used …
Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate
Predicting the penetration rate is a complex and challenging task due to the interaction
between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the …
between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the …
[HTML][HTML] Air pollution prediction using LSTM deep learning and metaheuristics algorithms
GI Drewil, RJ Al-Bahadili - Measurement: Sensors, 2022 - Elsevier
Air pollution is a leading cause of health concerns and climate change, one of humanity's
most dangerous problems. This problem has been exacerbated by an overabundance of …
most dangerous problems. This problem has been exacerbated by an overabundance of …
A novel particle swarm optimization-based grey model for the prediction of warehouse performance
Warehouses constitute a key component of supply chain networks. An improvement to the
operational efficiency and the productivity of warehouses is crucial for supply chain …
operational efficiency and the productivity of warehouses is crucial for supply chain …
A new auto-tuning model for predicting the rock fragmentation: a cat swarm optimization algorithm
The main focus of the present work is to offer an auto-tuning model, called cat swarm
optimization (CSO), to predict rock fragmentation. This population-based method has a …
optimization (CSO), to predict rock fragmentation. This population-based method has a …
Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance
A proper planning schedule for tunnel boring machine (TBM) construction is considered as a
necessary and difficult task in tunneling projects. Therefore, prediction of TBM performance …
necessary and difficult task in tunneling projects. Therefore, prediction of TBM performance …
[HTML][HTML] Blast-induced ground vibration prediction in granite quarries: An application of gene expression programming, ANFIS, and sine cosine algorithm optimized …
Blasting of rocks has intrinsic environmental impacts such as ground vibration, which can
interfere with the safety of lives and property. Hence, accurate prediction of the …
interfere with the safety of lives and property. Hence, accurate prediction of the …
Prediction of air-overpressure induced by blasting using an ANFIS-PNN model optimized by GA
Blasting operations typically have several negative impacts upon human beings and
constructions in adjacent region. Among all, air-overpressure (AOp) has been persistently …
constructions in adjacent region. Among all, air-overpressure (AOp) has been persistently …
Forecasting of TBM advance rate in hard rock condition based on artificial neural network and genetic programming techniques
The efficiency of tunnel boring machine (TBM) is regarded as a key factor in successfully
undertaking any mechanical tunneling project. In fact, an accurate forecasting of TBM …
undertaking any mechanical tunneling project. In fact, an accurate forecasting of TBM …
Computational intelligence model for estimating intensity of blast-induced ground vibration in a mine based on imperialist competitive and extreme gradient boosting …
In this paper, we developed a novel hybrid model ICA–XGBoost for estimating blast-
produced ground vibration in a mine based on extreme gradient boosting (XGBoost) and …
produced ground vibration in a mine based on extreme gradient boosting (XGBoost) and …