THE EFFECTIVENESS OF GENETIC ALGORITHM IN CAPTURING CONDITIONAL NONLINEAR OPTIMAL PERTURBATION WITH PARAMETERIZATION “ON-OFF” SWITCHES INCLUDED BY A MODEL

In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint method from providing correct gradient during the optimization process. To address this problem, the capture of CNOP, when the "on-off" switches are included in models, is treated as non-smooth optimization in this study, and the genetic algorithm (GA) is introduced. After detailed algorithm procedures are formulated using an idealized model with parameterization "on-off" switches in the forcing term, the impacts of "on-off" switches on the capture of CNOP are analyzed, and three numerical experiments are conducted to check the effectiveness of GA in capturing CNOP and to analyze the impacts of different initial populations on the optimization result. The result shows that GA is competent for the capture of CNOP in the context of the idealized model with parameterization ‘on-off’ switches in this study. Finally, the advantages and disadvantages of GA in capturing CNOP are analyzed in detail.

A novel conditional diagnosability algorithm under the PMC model

Conditionally t-diagnosable and t-diagnosable are important in system level diagnosis. Therefore,it is valuable to identify whether the system is conditionally t-diagnosable or t-diagnosable and derive the corresponding conditional diagnosability and diagnosability. In the paper,distinguishable measures of pairs of distinct faulty sets with a new perspective on establishing functions are focused.Applying distinguishable function and decision function,it is determined whether a system is conditionally t-diagnosable( or t-diagnosable) or not under the PMC( Preparata,Metze,and Chien)model directly. Based on the decision function,a novel conditional diagnosability algorithm under the PMC model is introduced which can calculate conditional diagnosability rapidly.

An intelligent automatic correlation method of oilbearing strata based on pattern constraints:An example of accretionary stratigraphy of Shishen 100 block in Shinan Oilfield of Bohai Bay Basin,East China

Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thickness,an intelligent automatic correlation method of oil-bearing strata based on pattern constraints is formed.We propose to introduce knowledge-driven in automatic correlation of oil-bearing strata,constraining the correlation process by stratigraphic sedimentary patterns and improving the similarity measuring machine and conditional constraint dynamic time warping algorithm to automate the correlation of marker layers and the interfaces of each stratum.The application in Shishen 100 block in the Shinan Oilfield of the Bohai Bay Basin shows that the coincidence rate of the marker layers identified by this method is over 95.00%,and the average coincidence rate of identified oil-bearing strata reaches 90.02% compared to artificial correlation results,which is about 17 percentage points higher than that of the existing automatic correlation methods.The accuracy of the automatic correlation of oil-bearing strata has been effectively improved.

Improved conditional differential attacks on lightweight hash family QUARK

Nonlinear feedback shift register(NFSR)is one of the most important cryptographic primitives in lightweight cryptography.At ASIACRYPT 2010,Knellwolf et al.proposed conditional differential attack to perform a cryptanalysis on NFSR-based cryptosystems.The main idea of conditional differential attack is to restrain the propagation of the difference and obtain a detectable bias of the difference of the output bit.QUARK is a lightweight hash function family which is designed by Aumasson et al.at CHES 2010.Then the extended version of QUARK was published in Journal of Cryptology 2013.In this paper,we propose an improved conditional differential attack on QUARK.One improvement is that we propose a method to select the input difference.We could obtain a set of good input differences by this method.Another improvement is that we propose an automatic condition imposing algorithm to deal with the complicated conditions efficiently and easily.It is shown that with the improved conditional differential attack on QUARK,we can detect the bias of output difference at a higher round of QUARK.Compared to the current literature,we find a distinguisher of U-QUARK/D-QUARK/S-QUARK/C-QUARK up to 157/171/292/460 rounds with increasing 2/5/33/8 rounds respectively.We have performed the attacks on each instance of QUARK on a 3.30 GHz Intel Core i5 CPU,and all these attacks take practical complexities which have been fully verified by our experiments.As far as we know,all of these results have been the best thus far.

AN OVERALL STUDY OF CONVERGENCE CONDITIONS FOR ALGORITHMS IN NONLINEAR PROGRAMMING

Since the point-to-set maps were introduced by Zangwill in the study of conceptual algorithms, various sufficient conditions for the algorithms to be of global convergence have been established.In this paper, the relations among all these conditions are illustrated by a unified approach;still more, unlike the sufficient conditions previously given in the literature,a new necessary condition is put forward at the end of the paper, so that it implies more applications.