ORELM: A Novel Machine Learning Approach for Prediction of Flyrock in Mine Blasting

Blast-induced flyrock is a hazardous and undesirable phenomenon that may occur in surface mines, especially when blasting takes place near residential areas. Therefore, accurate prediction of flyrock distance is of high significance in the determination of the statutory danger area. To this end, there is a practical need to propose an accurate model to predict flyrock. Aiming at this topic, this study presents two machine learning models, including extreme learning machine (ELM) and outlier robust ELM (ORELM), for predicting flyrock. To the best of our knowledge, this is the first work that investigates the use of ORELM model in the field of flyrock prediction. To construct and verify the proposed ELM and ORELM models, a database including 82 datasets has been collected from the three granite quarry sites in Malaysia. Additionally, artificial neural network (ANN) and multiple regression models were used for comparison. According to the results, both ELM and ORELM models performed satisfactorily, and their performances were far better compared to the performances of ANN and multiple regression models.

     

Estimating trends of the Mediterranean Sea level changes from tide gauge and satellite altimetry data (1993-2015)

The impact of climate change on sea level has received a great deal of attention by scientists worldwide.In this context,the problem of sea levels on global and regional scales have been analyzed in a number of studies based on tide gauges observations and satellite altimetry measurements.This study focuses on trend estimates from 18 high-quality tide gauge stations along the Mediterranean Sea coast.The seasonal Mann-Kendall test was run at a 5% significance level for each of the 18 stations for the period of 1993-2015(satellite altimetry era).The results of this test indicate that the trends for 17 stations were statistically significant and showed an increase(no significant trend was observed only at one station).The rates of sea level change for the 17 stations that exhibit significant trends,estimated using seasonal Sen's approach,range after correction for Vertical Land Motion(VLM)from 1.48 to 8.72 mm/a for the period1993-201 5.Furthermore,the magnitude of change at the location of each tide gauge station was estimated using the satellite altimetry measurements.Thus,the results obtained agree with those from the tide-gauge data analysis.     

Estimating trends of the Mediterranean Sea level changes from tide gauge and satellite altimetry data (1993-2015)

The impact of climate change on sea level has received a great deal of attention by scientists worldwide. In this context, the problem of sea levels on global and regional scales have been analyzed in a number of studies based on tide gauges observations and satellite altimetry measurements. This study focuses on trend estimates from 18 high-quality tide gauge stations along the Mediterranean Sea coast. The seasonal Mann-Kendall test was run at a 5% significance level for each of the 18 stations for the period of 1993-2015 (satellite altimetry era). The results of this test indicate that the trends for 17 stations were statistically significant and showed an increase (no significant trend was observed only at one station). The rates of sea level change for the 17 stations that exhibit significant trends, estimated using seasonal Sen's approach, range after correction for Vertical Land Motion (VLM) from 1.48 to 8.72 mm/a for the period 1993-2015. Furthermore, the magnitude of change at the location of each tide gauge station was estimated using the satellite altimetry measurements. Thus, the results obtained agree with those from the tide-gauge data analysis.     

An analytical approach to capture zone delineation for a well near a stream with a leaky layer

Abstract

An analytical solution is developed to delineate the capture zone of a pumping well in an aquifer with a regional flow perpendicular to a stream, assuming a leaky layer between the stream and the aquifer. Three different scenarios are considered for different pumping rates. At low pumping rates, the capture zone boundary will be completely contained in the aquifer. At medium pumping rates, the tip of the capture zone boundary will intrude into the leaky layer. Under these two scenarios, all the pumped water is supplied from the regional groundwater flow in the aquifer. At high pumping rates, however, the capture zone boundary intersects the stream and pumped water is supplied from both the aquifer and the stream. The two critical pumping rates which separate these three scenarios, as well as the proportion of pumped water from the stream and the aquifer, are determined for different hydraulic settings.

Editor D. Koutsoyiannis; Associate editor A. Koussis

Citation Asadi-Aghbolaghi, M., Rakhshandehroo, G.R., and Kompani-Zare, M., 2013. An analytical approach to capture zone delineation for a well near a stream with a leaky layer. Hydrological Sciences Journal, 58 (8), 1813–1823.     

Band Selection and Dimension Estimation for Hyperspectral Imagery—a New Approach Based on Invasive Weed Optimization

Currently, hyperspectral images have potential applications in many scientific areas due to the high spectral resolution. Extracting suitable and adequate bands/features from high dimensional data is a crucial task to classify such data. To overcome this issue, dimension reduction techniques have direct effects to improve the efficiency of classifiers on hyperspectral images. One common approach for decreasing the dimensionality is the feature/band selection by considering the optimum dimensionality of the hyperspectral imagery. In this paper, a new method was proposed to select optimal band for classification application, based on a metaheuristic Invasive Weed Optimization (IWO) algorithm. In this regard, the K-nearest neighbour (K-NN) technique was used as the classifier. Moreover, as a by-product of our band selection method, a new method was proposed to estimate an optimum dimension of the reduced hyperspectral images for better classification. Experimental results over three real-world hyperspectral datasets clearly showed that the proposed IWO-based band selection algorithm of this study led to the significant progress in selecting suitable bands for classification applications and estimation of optimum dimensionality of these datasets. In this regard, the overall accuracy (OA) of classification of the proposed IWO-based band selection algorithm was 92.02, 93.57, and 89.72 % for each dataset, respectively. Moreover, results reveal the superiority of the proposed IWO-based band selection algorithm against the other algorithms including GA, SA, ACO, and PSO for band selection purpose.     

Collaborative personalized multi‐criteria wayfinding for wheelchair users in outdoors

While finding the optimal route for users with physical disabilities and personalizing routes for each user, on the one hand, and collaborative wayfinding, on the other hand, have been addressed in the pedestrian navigation systems literature, there has not been much research on combining the two activities. The problem associated with wayfinding approaches solely based on information about network segments and personal preferences is that the information about segments in the database may not, correctly and/or adequately address user preferences. The problem associated with wayfinding approaches solely based on the ratings given to routes by wheelchair users is the lack of rates (or scores) for all possible routes between all possible origin‐destination pairs in the network. This article discusses an approach to combine these two approaches for wayfinding to augment each other's shortcomings. To evaluate the personalized wayfinding approach, we utilize a route index, called a comparison index. The results show that with a P‐value of 9%, the routes obtained from our approach are more accessible than the routes obtained from another approach developed in another study. To evaluate the collaborative wayfinding approach, a Monte Carlo simulation was conducted which reflects the updates in routes as users' feedbacks become available.