Hyongdoo Jang

Review article: A review of soft computing technology applications in several mining problems

Soft computing (SC) is a field of computer science that resembles the processes of the human brain. While conventional hard computing is run based on crisp values and binary numbers, SC uses soft values and fuzzy sets. In fact, SC technology is capable of address imprecision and uncertainty. The application of SC techniques in the mining industry is fairly extensive and covers a considerable number of applications. This paper provides a comprehensive overview of the published work on SC applications in different mining areas. A brief introduction to mining and the general field of SC applications are presented in the first section of the paper. The second section comprises four review chapters. Mining method selection, equipment selection problems and their applications in SC technologies are presented in chapters one and two. Chapter three discusses rock mechanics-related subjects and some of representative SC applications in this field. The last chapter presents rock blasting related SC applications that include blast design and hazards. The final section of the paper comments on the use of SC applications in several mining problems and possible future applications of advanced SC technologies.

Energy consumption modeling using artificial neural networks: The case of the world’s highest consumers

ABSTRACT The world’s highest energy consumer (HC) countries currently constitute around 62% of the world energy consumption. Therefore, it is highly important to model their energy consumption to obtain an estimated profile of future world energy consumption. In this study the HCs’ energy consumptions are modeled using artificial neural networks (ANNs). The models are developed based on economic and demographic variables, which are gross domestic product, population, import, and export of the countries selected. Performance of the derived models is assessed using mean absolute percentage error (MAPE), mean absolute error (MAE) and root mean square error (RMSE) for the testing data. The contribution rate of each variable to the HCs’ energy consumption are also determined to demonstrate the governing variables on the energy consumption. The results show that the correlation coefficients between the ANN predictions and actual energy consumptions are higher than 90%. This indicates a high reliability of the models for forecasting future energy consumption of the HC. Additionally, MAPE, MAE and RMSE values indicate that the ANN models can give adequate forecasting for the HCs’ energy consumption. Furthermore, contribution rates of input variables on energy consumption also indicate that energy consumption of each country studied is governed by different variables. It is expected that this study will be helpful for developing highly applicable energy policies for the HC countries. Furthermore, the results of this study can also be used for determining future trends in the global energy demand.

Support characteristics of eco-spiral pile with respect to twisting angle and ratio of borehole diameter to pile width

Abstract This study numerically analysed the characteristics of eco-spiral piles (Eco-SPs) as multi-purpose geotechnical supports. The behaviour of eco-spiral piles in the ground was studied with respect to their twisting angle and the ratio of borehole diameter to eco-spiral pile width using FLAC-3D based on the finite-difference method. A cement mortar grout was modelled to sustain the eco-spiral pile in a sandy soil. Relationships were found among the eco-spiral pile’s twisting angle, pull-out load and maximum shear stress. The results should aid the further design of the bolts for application in a range of circumstances.

A Multimedia Data Visualization Based on Ad Hoc Communication Networks and Its Application to Disaster Management

After massive earthquakes and other large-scale disasters, existing communication infrastructure may become unavailable and, therefore, it can be quite difficult for relief organizations to fully grasp the impact of the disaster on the affected region. Consequently, this will be the cause of delays to offer the strategic assistance, and to provide water and food, etc. In order to solve the problem of re-establishing communication infrastructure to allow for information gathering, we developed an ad hoc mobile communications network for disaster-struck areas using ZigBee. As the communication speed of ZigBee is low, we propose a problem-specific image compression method for the multimedia data visualization. By using the proposed method combined with GPS information, it is possible to quickly grasp the damage situation in the region. Through our communication experiments in Tsukuba City, Japan we confirm the effectiveness of our system as a disaster information gathering and management system.