On the basis of the shifting process of automated mechanical transmissions (AMTs) for traditional hybrid electric vehicles (HEVs), and by combining the features of electric machines with fast response speed, the dynamic model of the hybrid electric AMT vehicle powertrain is built up, the dynamic characteristics of each phase of shifting process are analyzed, and a control strategy in which torq...

This research presents a novel approach to solve m-machine no-wait flowshop scheduling problem. A continuous flowshop problem with total flowtime as criterion is considered applying a hybrid evolutionary algorithm. The performance of the proposed method is evaluated and the results are compared with the best known in the literature. Experimental tests show the superiority of the evolutionary hy...

Neuroscientists have long relished the possibility of using brain signals to control artificial devices. Already, in literature there are several devices such as brain-actuated technology, neuroprosthes or neurorobots collectively refer as hybrid brain machine interfaces (HBMI) [1]. The word hybrid means a continuous interaction between living brain and artificial electronic devices. HBMI uses ...

The widespread availability of machine understandable information on the Semantic Web offers some opportunities to improve traditional search. In this paper, we propose a hybrid web search architecture-HWS, which combines text search with semantic search to improve precision and recall. The components in HWS are described in detail, including several novel algorithms proposed to support the hyb...

In this paper, we proposed a novel hybrid group method of data handling least squares support vector machine (GLSSVM) algorithm, which combines the theory a group method of data handling (GMDH) with the least squares support vector machine (LSSVM). With the GMDH is used to determine the inputs of LSSVM method and the LSSVM model which works as time series forecasting. The aim of this study is t...

Engineers and researchers in the automobile industry have tried to design and build safer automobiles, but traffic accidents are unavoidable. Patterns involved in dangerous crashes could be detected if we develop a prediction model that automatically classifies the type of injury severity of various traffic accidents. These behavioral and roadway patterns are useful in the development of traffi...

Transport mode information is essential for understanding people’s movement behavior and travel demand estimation. Current approaches extract travel information once the travel is complete. Such approaches are limited in terms of generating just-in-time information for a number of mobility based applications, e.g., real time mode specific patronage estimation. In order to detect the transport m...

Assuring secure and reliable operation of networks has become a priority research area these days because of ever growing dependency on network technology. Intrusion detection systems (IDS) are used as the last line of defence. IDS identifies patterns of known intrusions (misuse detection) or differentiates anomalous network data from normal data (anomaly detection). In this paper, a novel Intr...

Researchers have embraced a variety of machine learning (ML) techniques in their efforts to improve the quality of learning programs. The recent evolution of hybrid architectures for machine learning systems has resulted in several approaches that combine rule-induction methods with case-based reasoning techniques to engender performance improvements over moretraditional one-representation arch...

In this paper, we address statistical machine translation of public conference talks. Modeling the style of this genre can be very challenging given the shortage of available in-domain training data. We investigate the use of a hybrid LM, where infrequent words are mapped into classes. Hybrid LMs are used to complement word-based LMs with statistics about the language style of the talks. Extens...