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Ball Mill

Ball mills are used primary for single stage fine grinding, regrinding, and as the second stage in two stage grinding circuits. According to the need of customers, ball mill can be either wet or dry designs. Ball mills have been designed in standard sizes of the final products between 0.074 mm and 0.4 mm in diameter.

Belt Conveyor

SBM delivers the world’s most comprehensive range of Heavy-duty conveyor belts. Base on more than 30 years of experience in development, manufacture and applications know-how, SBM designed the unique belts and belt systems to meet specific end-user requirements for high performance and cost-efficiency.

BWZ Heavy Duty Apron Feeder

BWZ series heavy duty apron feeder designed by SBM is one new type high-efficiency conveying equipments. It absorbs SBM decades years’ experience in designing &manufacturing conveying machines and the advanced technology of the world. This apron feeder is especially suitable for short-distance transmission.

CS Cone Crusher

Comparing with other kinds of crushers, CS Series spring cone crusher is quite excellent in hard material crushing and the final product has good sharp. The innovations like stable lubrication system and excellent sealing system evidently reduce the production cost, helping you to achieve the highest level of profitability.

Flotation Machine

With the development of mining industry, investors present various requirements of the features of flotation machine. Now there are many kinds of flotation machines, such as agitator flotation machine, pneumatic flotation machine and pneumatic- agitator flotation machine. And different mineral ores have different hydrophilicity, so the final configurations greatly depend on the professional designs.

Hammer Crusher

Hammer crusher designed by SBM fits for producing 0-3MM coarse powder products. This machine adopts theories of traditional crushing machines and grinding mills. It makes up the shortage of common mills, and it is the best choice to produce coarse powder at big capacity.

High-frequency Screen

Compared with the commonly screening and grading equipments, the High-frequency screen adopts higher frequency. As a result, it is able to damage tension force of the pulp surface. Also the fine particles are able to oscillate speedily on the surface of the screen because of the high frequency, and the big expecting minerals are isolated from the pulp easily.

HJ Series Jaw Crusher

By analyzing customers’ requirements and absorbing the world-class advanced technology, SBM developed the HJ series jaw crusher. This machine has larger capacity but the energy consumption is quite low. It is to be the ideal substitute products for old ones.

Mining association rules from stars

Eric Ka Ka Ng, Ada Wai-Chee Fu, Ke Wang+ Chinese University of Hong Kong Depar. Association rules mining [AIS93, AS94] is identified as one of the important problems i.

Directed Graph-based Frequent Itemsets Mining Association Rules .

This paper proposes a frequent itemsets algorithm of mining association rules based on. WU Hong-xia,XIE Qiang(Faculty of Information Science and Technology,Nanjing Univers.

Research on Mining Association Rules in Road Traffic Accidents--《.

6 YANG Bing Ru ①, SUN Hai Hong ①, and XIONG Fan Lun ② ①(School of Information. MINING QUANTITATIVE ASSOCIATION RULES WITH STANDARD SQL QUERIES AN.

Efficient mining of association rules in distributed databases.

Publication » Efficient mining of association rules in distributed databases. Efficient mining of association rules in distributed databases Dept. of Comput. Sci., Hong Kong Univ.

Asynchronous Parallel Algorithm for Mining Association Rules on a .

Mining association rules from large databases is an important problem in data mining. T. The research of the ?rst author are supported in part by RGC (the Hong Kong Research.

.- Citation Query Scalable Parallel Data Mining for Association Rules

Scalable Parallel Data Mining for Association Rules (1997) by Eui-Hong (Sam) Han, Ge. Exploratory Mining and Pruning Optimizations of Constrained Associations Rules by Ra.

Mining Trading Rules from Stock Time Series Based on Charting .

This paper proposes a method by which investors can acquire some trading rules from s. Data mining for geo-information of urban land utility:the case of Shanghai[J];Geographic.

.and number of rules for fuzzy mining from quantitative data-

making the processing time reduced. The fuzzy association rules derived in this way are not complete. This paper thus modifies it and proposes a new fuzzy data-mining algorithm.

The Research of Mining Association Rules Between Personality and .

Publication » The Research of Mining Association Rules Between Personality and Beh. 4th International Conference, Hong Kong, China, July 31 - August 3, 2005, Proceedings .

mining staff assignment rules from event-based data-.

we introduce the problem of mining staff assignment rules and show that it can be interp. [7] Shyue-Liang Wang Chun-Yin Kuo Tzung-Pei Hong Mining Fuzzy Similar Association .

Flexible Mining of Association Rules: Library and Information Science .

Shen, Hong. Flexible Mining of Association Rules. Encyclopedia of Data Warehousing and Mining, Second Edition. IGI Global, 2009. 890-894. Web. 5 Oct. 2014. doi:10.4018/97.

Mining fuzzy association rules from low-quality data - Springer

Hong, T, Kuo, C, Chi, S (2001) Trade-off between time complexity and number of rules for fuzzy mining from quantitative data. Int J Uncertain Fuzziness Knowl Based Syst 9: pp. 5.

CiteSeerX - Mining Association Rules with Multiple Minimum .

by Yeong-chyi Lee A, Tzung-pei Hong B, Wen-yang Lin C BibTeX @MISC{A_mininga. title = {Mining Association Rules with Multiple Minimum Supports Using Maximum Const.

regular paper mining quantitative rules in a software project data set-.

then rules are merged after mining so that adjacent partitions are combined. The paper . [4] Tzung-Pei Hong;Chan-Sheng Kuo;Sheng-Chai Chi;Shyue-Liang Wang Mining Fuzzy .

a prefix tree-based model for mining association rules from .

we deal with the problem of mining temporal association rules in stock databases conta. [3] Shyue-Liang Wang Chun-Yin Kuo Tzung-Pei Hong Mining Fuzzy Similar Association .

HKEx: New Listing Rules For Mining And Petroleum Companies.

Chapter 18 of the listing rules of the Hong Kong Stock Exchange ( Listing Rules ) applie. development and mining production activities and a summary of expenditure incurred on.

mining fuzzy association rules from questionnaire data-.

interesting association rules that would have never been found by previous mining algori. [3] Shyue-Liang Wang Chun-Yin Kuo Tzung-Pei Hong Mining Fuzzy Similar Association .

genminer: mining informative association rules from genomic data-.

rules. GENMINER facili- tates the integration : : Genminer: Mining Inf. Abstract: GENMINER is a smart adaptation of closed itemsets based association rules .

THE MFFP-TREE FUZZY MINING ALGORITHM TO DISCOVER .

thus making the mined fuzzy rules a little difficult to understand. Lin, Hong, and Lu (2010)proposed the fuzzy FP-tree algorithm for constructing and mining fuzzy association rules b.

Mining association rules with weighted items - ResearchGate

Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin DOI: 10.1109/IDEAS. mining is most commonly used in attempts to induce association rules from transaction d.

.on Negative Association Rules Mining Algorithms [10005698228].

Research on Negative Association Rules Mining Algorithms ZHU Hong-lei,XU Zhi-gang,LI Ming(College of Electrical and Information Engineering,Lanzhou University of Technolog.

Data Mining Using Rules Extracted from SVM: An Application to .

Usama, F., Piatetsky-Shapiro, G., Smyth, P.: From Data Mining to Knowledge Discover. Mining, KDD 2006 (2006) About this Chapter Data Mining Using Rules Extracted from .

An algorithm for mining association rules with multiple minimum .

5 LEI Hong-yan1,2, ZOU Han-bin2 (1 College of Computer Science and Technology, Hu. Parallel mining algorithm for fuzzy association rules[J];Journal of Southeast University (N.

Algorithm for Mining Weighted Association Rules Based On Record .

2 MA Yuan Yuan, SUN Zhi Hui, and GAO Hong Mei (Department of Computer Science &. Algorithm based on Rough Set for mining default weighted rules[J];Journal of Southeast .

Exploring Fuzzy Ontologies in Mining Generalized Association Rules.

The most common use of fuzzy taxonomies in mining generalized association rules occu. Hong, T.P., Lin, K.Y., Wang, S.L.: Fuzzy data mining for interesting generalized associat.

Assocaition Rules Mining Algorithm Based on Transaction Matrix--《.

On the basis of the classical algorithm for mining association rules,an improved algorithm. 6 Liu , Wang Chong-Jun, Xie Jun-Yuan(State Key Laboratory for Novel Techn.

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