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Author(s):  
L.K. Miroshnikova ◽  
A.Yu. Mezentsev ◽  
G.A. Kadyralieva ◽  
M.A. Perepelkin

The Zhdanovskoe copper-nickel sulfide ores deposit is located in the north-west of the Murmansk region and is a mineral raw material source for JSC «Kola MMC». The main mining method used is sublevel caving. In some areas, due to the complex shape of the ore bodies, the open stoping mining method is used which requires determining stable parameters of stopes and pillars. It is necessary to study the stress-strain state of the deposit to ensure safe mining conditions. One of the possible solutions is the modeling of the stress-strain state of rock mass using the finite element method, for example, CAE Fidesys, which is FEMbased software. The use of CAE Fidesys for solving geomechanics tasks allows creating models of individual excavation units to determine the stability of stopes and pillars, and large-scale models that include several ore bodies and areas of the host rock mass. The article considers solutions of both types of geomechanic tasks using CAE Fidesys for conditions of the Zhdanovskoe deposit.


Minerals ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 88
Author(s):  
Haoxuan Yu ◽  
Shuai Li ◽  
Xinmin Wang

With the continuous innovation and development of science and technology, the mining industry has also benefited greatly and improved over time, especially in the field of backfill mining. Mining researchers are increasingly working on cutting-edge technologies, such as applying artificial intelligence to mining production. However, in addition, some problems in the actual engineering are worth people’s attention, and especially in China, such a big mining country, the actual engineering faces many problems. In recent years, Chinese mining researchers have conducted a lot of studies on practical engineering problems in the stope and goaf of backfill mining method in China, among which the three most important points are (1) Calculation problems of backfill slurry transportation; (2) Reliability analysis of backfill pipeline system; (3) Stope backfill process and technology. Therefore, this final part (Part III) will launch the research progress of China’s practical engineering problems from the above two points. Finally, we claim that Part III serves just as a guide to starting a conversation, and hope that many more experts and scholars will be interested and engage in the research of this field.


Author(s):  
Yafei Wang

Through big data mining, enterprises can deeply understand the consumer preferences, behavior characteristics, market demand and other derived data of customers, so as to provide the basis for formulating accurate marketing strategies. Therefore, this paper proposes a marketing management big date mining method based on deep trust network model. This method first preprocesses the big data of marketing management, including data cleaning, data integration, data transformation and data reduction, and then establishes a big data mining model by using deep trust network to realize the research on the classification of marketing management data. Experimental results show that the proposed method has 99.08% accuracy, the capture rate reaches 88.11%, and the harmonic average between the accuracy and the recall rate is 89.27%, allowing for accurate marketing strategies.


2022 ◽  
Vol 20 (4) ◽  
pp. 296
Author(s):  
Elsa Pansilvania Andre Manjate ◽  
Mahdi Saadat ◽  
Hisatoshi Toriya ◽  
Fumiaki Inagaki ◽  
Youhei Kawamura

2022 ◽  
Vol 14 (2) ◽  
pp. 635
Author(s):  
Ahmed M. A. Shohda ◽  
Mahrous A. M. Ali ◽  
Gaofeng Ren ◽  
Jong-Gwan Kim ◽  
Mohamed Abd-El-Hakeem Mohamed

Decision-making is very important in many fields, such as mining engineering. In addition, there has been a growth of computer applications in all fields, especially mining operations. One of these application fields is mine design and the selection of suitable mining methods, and computer applications can help mine engineers to decide upon and choose more satisfactory methods. The selection of mining methods depends on the rock-layer specification. All rock characteristics should be classified in terms of technical and economic concerns related to mining rock specifications, such as mechanical and physical properties, and evaluated according to their weights and ratings. Methodologically, in this study, the criteria considered in the University of British Columbia (UBC) method were used as references to establish general criteria. These criteria consist of general shape, ore thickness, ore plunge, and grade distribution, in addition to the rock quality designation (ore zone, hanging wall, and foot wall) and rock substance strength (ore zone, hanging wall, and foot wall). The technique for order of preference by similarity to ideal solution (TOPSIS) was adopted, and an improved TOPSIS method was developed based on experimental testing and checked by means of the application of cascade forward backpropagation neural networks in mining method selection. The results provide indicators that decision makers can use to choose between different mining methods based on the total points given to all ore properties. The best mining method is cut and fill stopping, with a rank of 0.70, and the second is top slicing, with a rank of 0.67.


SinkrOn ◽  
2022 ◽  
Vol 7 (1) ◽  
pp. 49-58
Author(s):  
Handhy Nur Prabowo ◽  
Resad Setyadi ◽  
Wahyu Adi Prabowo

Indonesia is a country with unique tourist destinations from each region. The tourism sector has an impact on the Indonesian economy which can encourage economic growth and increase the country's foreign exchange from foreign tourist visits. Tourism growth in Indonesia was disrupted due to the Covid-19 pandemic with the imposition of major social restrictions which resulted in a decrease in tourist visits and the paralysis of the tourism sector. Based on the problems described above, the authors are interested in conducting research in order to classify data on foreign tourist arrivals based on the entrance of foreign tourist arrivals. This research uses data mining method and K-Means Algorithm to form 5 clusters. The 5 clusters are divided into groups of tourist entrances which are categorized as very high (C1), high (C2), moderate (C3), low (C4) and very low (C5). In forming the 5 clusters, the researchers used Ms. Excel and Rapidminer 10.1 to process data. The results of this study obtained that the tourist entrance group was categorized as very high (C1) with 1 data, high (C2) with 1 data, moderate (C3) with 1 data, low (C4) with 1 data and very low (C5). ) that is with 21 data. This study aims to provide suggestions and future considerations to the Ministry of Tourism and Creative Economy of the Republic of Indonesia (Kemenparekraf) to carry out policies so that the Indonesian tourism sector can return to normal.


2022 ◽  
pp. 247-269
Author(s):  
Ozan Çatir

The satisfaction of guests is of paramount importance to ensure the continuity and profitability of hotels. This study aims to determine guests' satisfaction with hotels by analyzing the online comments of guests. The text mining method has been utilized in this study. 58,193 Turkish comments about 5-star hotels in Turkey have been examined. These comments have been subjected to frequency and association analysis by models with Rapid Miner program. It may be stated that the guests are satisfied with 5-star hotel management in Turkey, and they are also satisfied with hotels in general and the services provided by hotels.


Author(s):  
Aleardo Junior Manacero ◽  
Renata Spolon Lobato ◽  
Marcos Antônio Cavenaghi ◽  
Alexandre Colombo ◽  
Roberta Spolon

2022 ◽  
Vol 32 (3) ◽  
pp. 1843-1854
Author(s):  
D. Palanikkumar ◽  
Kamal Upreti ◽  
S. Venkatraman ◽  
J. Roselin Suganthi ◽  
Sridharan Kannan ◽  
...  

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