排序方式: 共有48条查询结果,搜索用时 15 毫秒
1.
Abbass Mohammed Y. Kwon Ki-Chul Kim Nam Abdelwahab Safey A. El-Samie Fathi E. Abd Khalaf Ashraf A. M. 《Artificial Intelligence Review》2021,54(5):3349-3360
Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial... 相似文献
2.
Abbass Sabour Mojtaba Jafarpour Mehrzad Ashrafpour 《Quantum Information Processing》2013,12(2):1287-1297
Dynamics of localizable entanglement in a qutrit chain, in the presence of the Dzyaloshinskii–Moriya (DM) interaction is studied. Three distinct initial states, namely, superposition of the ground and the first excited state (SGE), a GHZ state and a superposition of qutrit coherent states (SQCS) are considered in this investigation. While the ground and the first excited state exhibit the maximum of entanglement, the latter is diminished for any superposition of the states. In both SGE and GHZ cases, localizable entanglement (LE) oscillates and its period is a decreasing function of the ratio of the strength of DM interaction and the spin coupling constant (DS ratio), but its maximum value is independent of the latter. In SQCS case, LE also oscillates in time at small values of DS ratio; its average is reduced as the strength of the DM interaction increases and gains its maximum average and the highest peaks at a specific value of the coherence parameter. 相似文献
3.
Bruno H. G. Barbosa Lam T. Bui Hussein A. Abbass Luis A. Aguirre Ant?nio P. Braga 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2011,15(9):1735-1747
This paper presents two new approaches for constructing an ensemble of neural networks (NN) using coevolution and the artificial
immune system (AIS). These approaches are extensions of the CLONal Selection Algorithm for building ENSembles (CLONENS) algorithm.
An explicit diversity promotion technique was added to CLONENS and a novel coevolutionary approach to build neural ensembles
is introduced, whereby two populations representing the gates and the individual NN are coevolved. The former population is
responsible for defining the ensemble size and selecting the members of the ensemble. This population is evolved using the
differential evolution algorithm. The latter population supplies the best individuals for building the ensemble, which is
evolved by AIS. Results show that it is possible to automatically define the ensemble size being also possible to find smaller
ensembles with good generalization performance on the tested benchmark regression problems. More interestingly, the use of
the diversity measure during the evolutionary process did not necessarily improve generalization. In this case, diverse ensembles
may be found using only implicit diversity promotion techniques. 相似文献
4.
Rule-based intrusion detection systems generally rely on hand crafted signatures developed by domain experts. This could lead to a delay in updating the signature bases and potentially compromising the security of protected systems. In this paper, we present a biologically-inspired computational approach to dynamically and adaptively learn signatures for network intrusion detection using a supervised learning classifier system. The classifier is an online and incremental parallel production rule-based system.A signature extraction system is developed that adaptively extracts signatures to the knowledge base as they are discovered by the classifier. The signature extraction algorithm is augmented by introducing new generalisation operators that minimise overlap and conflict between signatures. Mechanisms are provided to adapt main algorithm parameters to deal with online noisy and imbalanced class data. Our approach is hybrid in that signatures for both intrusive and normal behaviours are learnt.The performance of the developed systems is evaluated with a publicly available intrusion detection dataset and results are presented that show the effectiveness of the proposed system. 相似文献
5.
Neural-Based Learning Classifier Systems 总被引:1,自引:0,他引:1
Dam H.H. Abbass H.A. Lokan C. Xin Yao 《Knowledge and Data Engineering, IEEE Transactions on》2008,20(1):26-39
UCS is a supervised learning classifier system that was introduced in 2003 for classification in data mining tasks. The representation of a rule in UCS as a univariate classification rule is straightforward for a human to understand. However, the system may require a large number of rules to cover the input space. Artificial neural networks (NNs), on the other hand, normally provide a more compact representation. However, it is not a straightforward task to understand the network. In this paper, we propose a novel way to incorporate NNs into UCS. The approach offers a good compromise between compactness, expressiveness, and accuracy. By using a simple artificial NN as the classifier's action, we obtain a more compact population size, better generalization, and the same or better accuracy while maintaining a reasonable level of expressiveness. We also apply negative correlation learning (NCL) during the training of the resultant NN ensemble. NCL is shown to improve the generalization of the ensemble. 相似文献
6.
Hussein A. Abbass 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2006,10(8):687-698
When an optimization problem encompasses multiple objectives, it is usually difficult to define a single optimal solution.
The decision maker plays an important role when choosing the final single decision. Pareto-based evolutionary multiobjective optimization (EMO) methods are very informative for the decision making process since they provide the decision maker with a set of efficient
solutions to choose from. Despite that the set of efficient solutions may not be the global efficient set, we show in this
paper that the set can still be informative when used in an interactive session with the decision maker. We use a combination
of EMO and single objective optimization methods to guide the decision maker in interactive sessions. 相似文献
7.
Abbass Allan; Arthey Stephen; Elliott Jason; Fedak Tim; Nowoweiski Dion; Markovski Jasmina; Nowoweiski Sarah 《Canadian Metallurgical Quarterly》2011,48(2):109
The advent of readily accessible, inexpensive Web-conferencing applications has opened the door for distance psychotherapy supervision, using video recordings of treated clients. Although relatively new, this method of supervision is advantageous given the ease of use and low cost of various Internet applications. This method allows periodic supervision from point to point around the world, with no travel costs and no long gaps between direct training contacts. Web-conferencing permits face-to-face training so that the learner and supervisor can read each other's emotional responses while reviewing case material. It allows group learning from direct supervision to complement local peer-to-peer learning methods. In this article, we describe the relevant literature on this type of learning method, the practical points in its utilization, its limitations, and its benefits. (PsycINFO Database Record (c) 2011 APA, all rights reserved) 相似文献
8.
9.
Alam S. Abbass H.A. Barlow M. 《Intelligent Transportation Systems, IEEE Transactions on》2008,9(2):209-225
In this paper, we introduce the air traffic operations and management simulator (ATOMS), which is an air traffic and airspace modeling and simulation system for the analysis of free-flight concepts. This paper describes the design, architecture, functionality, and applications of the ATOMS. It is an intent-based simulator that discretizes the airspace in equal-sized hyper-rectangular cells to maintain intent reference points. It can simulate end-to-end airspace operations and air navigation procedures for conventional air traffic, as well as for free flight. Atmospheric and wind data that are modeled in the ATOMS result in accurate trajectory predictions. The ATOMS uses a multiagent-based modeling paradigm for modular design and easy integration of various air traffic subsystems. A variety of advanced air traffic management (ATM) concepts that are envisioned in free flight are prototyped in the ATOMS, including airborne separation assurance (ASA), cockpit display of traffic information (CDTI), weather avoidance, and decision support systems (DSSs). Experimental results indicate that advanced ATM concepts make a sound case for free flight; however, there is a need to investigate and understand their complex interaction under nonnominal scenarios. 相似文献
10.
Thermally Resistive Electrospun Composite Membranes for Low‐Grade Thermal Energy Harvesting 下载免费PDF全文
Syed Waqar Hasan Suhana Mohd. Said Mohd. Faizul Mohd Sabri Hasan Abbass Jaffery Ahmad Shuhaimi Bin Abu Bakar 《大分子材料与工程》2018,303(3)
In this work, thermally insulating composite mats of poly(vinylidene fluoride) (PVDF) and polyacrylonitrile (PAN) blends are used as the separator membranes. The membranes improve the thermal‐to‐electrical energy conversion efficiency of a thermally driven electrochemical cell (i.e., thermocell) up to 95%. The justification of the improved performance is an intricate relationship between the porosity, electrolyte uptake, electrolyte uptake rate of the electrospun fibrous mat, and the actual temperature gradient at the electrode surface. When the porosity is too high (87%) in PAN membranes, the electrolyte uptake and electrolyte uptake rate are significantly high as 950% and 0.53 µL s?1, respectively. In such a case, the convective heat flow within the cell is high and the power density is limited to 32.7 mW m?2. When the porosity is lesser (up to 81%) in PVDF membranes, the electrolyte uptake and uptake rate are relatively low as 434% and 0.13 µL s?1, respectively. In this case, the convective flow shall be low, however, the maximum power density of 63.5 mW m?2 is obtained with PVDF/PAN composites as the aforementioned parameters are optimized. Furthermore, multilayered membrane structures are also investigated for which a bilayered architecture produces highest power density of 102.7 mW m?2. 相似文献