The molten steel temperature in ladle furnace is a significant variable, but it is hard to be measured by real-time detection, which has some bad effects on productions. Soft sensors are alternative and effective tech...
详细信息
The molten steel temperature in ladle furnace is a significant variable, but it is hard to be measured by real-time detection, which has some bad effects on productions. Soft sensors are alternative and effective techniques to solve this issue. In this paper, the soft sensor of the molten steel temperature established by the Modified Maximum Entropy based Pruned Bootstrap Feature Subsets Ensemble (MMEP-BFSE) method is proposed. Although the Bootstrap Feature Subsets Ensemble (BFSE) temperature model is prominent in the precision and the forecasting speed on the large-scale and noisy data, its main drawback is too many sub-models required to combine, which is not always feasible for applications. To alleviate this drawback, the Modified Maximum Entropy based Pruning (MMEP) approach is presented, in which a subset of sub-models that better approximates the complete ensemble is find based on the maximum Rényi entropy and the trade-off parameter between the precision and the diversity of sub-models. Then, the soft sensor of the temperature based on the MMEP-BFSE is established on the practical data. Experiments show that the proposed soft sensor outperforms the others in the precision, and meets the precision requirements. Sub-models of the BFSE temperature model are substantially pruned with improved generalization by the MMEP approach.
As their scales and complexities increase, the computer-based network systems suffer from increasing probability of being intruded or crashed and decreasing dependability. Such a problem can be solved by extending the...
详细信息
Most of the existing secret sharing schemes are constructed to realize general access structure, which is defined in term of authorized groups of participants, and is unable to be applied directly to the design of an ...
详细信息
Most of the existing secret sharing schemes are constructed to realize general access structure, which is defined in term of authorized groups of participants, and is unable to be applied directly to the design of an intrusion tolerant system. Instead, the generalized adversary structure, which specifies the corruptible subsets of participants, can be determined directly by exploiting the system setting and the attributes of all participants. An efficient secret sharing scheme realizing graph-based adversary structures is proposed. The scheme requires less computational costs and storage overhead than the existing ones. Furthermore, it is proved that the scheme satisfy both the required properties of the secret sharing scheme, i.e., the reconstruction property and the perfect property.
A secret sharing scheme for generalized adversary structure is a method of sharing a secret among a finite set of participants in such a way that only certain pre-specified subsets of participants cannot recover the s...
详细信息
ISBN:
(纸本)0780386477
A secret sharing scheme for generalized adversary structure is a method of sharing a secret among a finite set of participants in such a way that only certain pre-specified subsets of participants cannot recover the secret. This paper proposes an efficient secret sharing scheme realizing generalized adversary structure, and proves that the scheme satisfy both reconstruction and perfect properties of the secret sharing. The main feature of this scheme is that it performs modular additions and subtractions only, and so can achieve lower computation cost. Then, the reduction on the scheme is done based on an equivalence relation defined over adversary structure. Analysis shows that reduced scheme still preserves the desired properties of original one.
暂无评论