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The classification of imbalanced data is a major challenge for machine learning. In this paper, we presented a fuzzy total margin based support vector machine (FTM-SVM) method to handle the class imbalance learning (CIL) problem in the presence of outliers and noise. The proposed method incorporates total margin algorithm, different cost functions and the proper approach of fuzzification of the penalty into FTM-SVM and formulates them in nonlinear case. We considered an excellent type of fuzzy membership functions to assign fuzzy membership values and got six FTM-SVM settings. We evaluated the proposed FTM-SVM method on two artificial data sets and 16 real-world imbalanced data sets. Experimental results show that the proposed FTM-SVM method has higher G_Mean and F_Measure values than some existing CIL methods. Based on the overall results, we can conclude that the proposed FTM-SVM method is effective for CIL problem, especially in the presence of outliers and noise in data sets. 相似文献
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浮选锑尾矿回收金的试验研究 总被引:1,自引:0,他引:1
明平田 《有色金属(选矿部分)》2011,1(4)
青海某锑金矿选矿厂采用"先锑后金"的优先浮选流程,因矿石氧化程度高,泥化现象严重,导致浮选金精矿品位及回收率很低。为了提高金的选矿回收率,对选锑尾矿采用CIL提金试验研究,金浸出率为65.10%,相比较原选矿工艺金回收率提高52.95%。 相似文献
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富氧炭浸提金工艺在哈德门金矿的应用 总被引:1,自引:1,他引:1
介绍了富氧炭浸提金工艺在哈德门金矿二期扩建工程中的应用。在不增加浸出设备的前提下,生产能力由一期的300t/d提高到600t/d,浸出时间由30h缩短为15h,氰化物消耗下降,而富氧前后浸出率相当;节省了基建投资,降低了生产成本。 相似文献
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二段磨矿是黄金炭浸厂生产中的关键环节,不仅影响生产技术指标,同时因其作业高能耗的特点,对选矿控制生产成本也起着至关重要的作用。通过对某金矿炭浸厂二段磨矿过程进行优化实践,取得了良好的效果;这说明在生产中重视磨矿过程技术参数的优化和磨矿过程的精细化操作,对提高炭浸厂的生产能力、节能降耗、降低生产成本、提高企业经济效益具有重要的现实意义。 相似文献
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为了提高青海某难选半氧化金矿的选矿回收率,在原矿工艺矿物学研究的基础上,开展了原矿浸出、浮选和浮选尾矿CIL浸出试验,并进行了环保提金剂和NaCN浸出对比试验研究。结果表明,在磨矿细度(-74 μm含量)为91.81%条件下,分别采用1#、2#环保提金剂和NaCN堤金,金的浸出率分别为80.07%、79.71%和80.80%;在磨矿细度(-74 μm含量)为83.64%条件下,采用浮选和浮选尾矿CIL浸出,获得浮选金精矿品位为125.94×10-6,浮选回收率为73.72%,浮选尾矿采用1#、2#环保提金剂和NaCN,选矿总回收率分别达到92.67%、93.62%和94.99%。 相似文献
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提高团结沟金矿选矿回收率的试验研究 总被引:3,自引:1,他引:3
通过对团结沟金矿原矿矿石性质、浮选尾矿、浮选精矿及浮选精矿浸渣特性的分析,对浮选精矿浸渣采用溜槽重选进行工业生产,溜槽重选精矿采用焙烧-CIL炭浸法或微生物氧化法提金,溜槽重选尾矿再浮选;浮选精矿焙烧,焙砂CIL炭浸法提金进行了介绍。建议采用重选法回收浮选尾矿中的细粒级自然金、黄铁矿及赋存在黄铁矿与脉石矿物连生体中的金,提高团结沟金矿总的选矿回收率。 相似文献
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Nicu G. Fruja 《Science of Computer Programming》2008,72(3):176-219
A crucial role in the Microsoft .NET Framework Common Language Runtime (CLR) security model is played by type safety of the Common Intermediate Language (CIL). In this paper, we formally prove type safety of a large subset of CIL. To do so, we begin by specifying the static and dynamic semantics of CIL by providing an abstract interpreter for CIL programs. We then formalize the bytecode verification algorithm, whose job it is to compute a well-typing for a given method. We then prove type safety of well-typed methods, i.e., the execution according to the semantics model of legal and well-typed methods does not lead to any run-time type violations. Finally, to prove CIL’s type safety, we show that the verification algorithm is sound, i.e., the typings it produces are well-typings, and complete, i.e., if a well-typing exists, then the algorithm computes one. 相似文献