Prediction of Load in Reverse Extrusion Process of Hollow Parts using Modern Artificial Intelligence Approaches

Extrusion is one of the important processes to manufacture and produce military and industrial components. Designing its tools is usually associated with trial and error and needs great expertise and adequate experience. Reverse extrusion process is known as one of the common processes for production of hollow parts with closed ends. The significant load required in formation of a workpiece is one of the existing constraints for the reverse extrusion process. This issue becomes rather difficult especially for the parts having thin walls since its analysis using finite element softwares is exposed to some limitations. In this regard, application of artificial intelligence for prediction of load in the reverse extrusion process will not only save time and money, but also improve quality features of the product. Based on the existing data and methods suggested for variations of punching force through the reverse extrusion process, the system is trained and then performance of the system is evaluated using the test data in this paper. Efficiency of the proposed method is also assessed via comparison with the results of others.DOI:http://dx.doi.org/10.11591/ijece.v4i3.535

An Improved Continuous-Action Extended Classifier Systems for Function Approximation

AbstractDue to their structural simplicity and superior generalization capability, Extended Classifier Systems (XCSs) are gaining popularity within the Artificial Intelligence community. In this study an improved XCS with continuous actions is introduced for function approximation purposes. The proposed XCSF uses “prediction zones,” rather than distinct “prediction values,” to enable multi-member match sets that would allow multiple rules to be evaluated per training step. It is shown that this would accelerate the training procedure and reduce the computational cost associated with the training phase. The improved XCSF is also shown to produce more accurate rules than the classical classifier system when it comes to approximating complex nonlinear functions

Adaptation of the application waspar to new linux distributions

Peer Reviewe

Intelligent Detection of Intrusion into Databases Using Extended Classifier System (XCS)

With increasing tendency of users to distributed computer systems in comparison with concentrat-ed systems, intrusion into such systems has emerged as a serious challenge. Since techniques of intrusion into systems are being intelligent, it seems necessary to use intelligent methods to en-counter them. Success of the intrusion systems depends on the strategy employed in these sys-tems for attack detection. Application of eXtended Classifier Systems (XCS) is proposed in this paper for detection of intrusions to databases. The extended classifier systems which are known as one of the most successful types of learning agents create a set of stochastic rules and com-plete them based on the methods inspired from human learning process. Thereby, they can grad-ually get a comprehensive understanding of the environment under study which enables them to predict the correct answer at an acceptable accuracy once encountered with new issues. The method suggested in this paper an improved version of extended classifier systems is “trained” using a set of existing examples in order to identify and avoid attempts to intrude computer sys-tems during phases of application and encountering these attempts. The proposed method has been tested on several problems to demonstrate its performance while its results indicate a 91% detection of various known intrusions to the databases.DOI:http://dx.doi.org/10.11591/ijece.v3i5.403

Time base stability of ocean bottom seismometers (OBS)

During the past decades, Ocean Bottom Seismometers (OBS) have played a key role in permanent seismic activity monitoring at sea as well as allowing a better understating of the earth interior. Data collected by the instrument can provide information on the ocean bottom sub-layers down to a depth of 40 km beneath the ocean floor. The accuracy of the results directly depends on the temperature stability of the crystal used as the main time base of the equipment. This paper presents the study of temperature stability of a Seascan module in real environmental conditions. By means of a climate chamber, temperature tests of a Seascan module were carried out and crystal temperature stability was calculated.Peer ReviewedPostprint (published version

Clock synchronization of a broadband seismometer through IEEE-1588 protocol

In seismology, the time of the signal acquisition is highly important in order to know the magnitude and location of the earthquake. This paper presents the tests carried out to synchronize the seismometer clock through the IEEE-1588 protocol.Peer ReviewedPostprint (published version