检索结果-内蒙古大学图书馆

4th International Conference on Intelligent Systems and Pattern Recognition, ISPR 2024

作者： Barzev, Iliyan Borissova, Daniela Institute of Information and Communication Technologies at the Bulgarian Academy of Sciences Sofia1113 Bulgaria

ISBN: (纸本)9783031821523

One of the essential factors in cyber defense is malware analysis. Attackers use various social engineering techniques along with one or more zero-day vulnerabilities to deploy malicious software. In this regard, various malware detection algorithms are being developed to deal with this type of threat faced not only by individual users but also by organizations/nations. Low classification accuracy, computational complexity, and resource usage are among the factors influencing malware evaluation methods. Therefore, our efforts are also focused on improving the detection and classification of malware. To this end, an improved static analysis approach for malware detection is proposed by optimizing feature extraction by combining different machine learning algorithms. Three hybrid algorithms based on the combination of Naive Bayes, K Nearest Neighbors, and Random Forest are defined. To measure the accuracy of these hybrid algorithms a proper formula is presented. The applicability of the proposed hybrid algorithms is tested on a subset of the IoT-23 dataset, generated by the Avast AIC laboratory using Zeek Net-work Security Monitor. The conducted experiments and the obtained results about the hybrid algorithms’ performance are not only accurate but also precise and reliable in detecting true positives while minimizing false positives and negatives. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Feature Extraction hybrid algorithms Malware Detection Static Analysis

来源：评论

学校读者我要写书评

暂无评论

Brief Announcement: On the I/O Complexity of Sequential and Parallel hybrid Integer Multiplication algorithms 22

Brief Announcement: On the I/O Complexity of Sequential and ...

引用

34th ACM Symposium on Parallelism in algorithms and Architectures (SPAA)

作者： De Stefani, Lorenzo Brown Univ Providence RI 02912 USA

ISBN: (纸本)9781450391467

Almost asymptotically tight lower bounds are derived for the Input/Output (I/O) complexity IOA(n, M) of a general class of hybrid algorithms computing the product of two integers, each represented with n digits in a given base s, in a two-level storage hierarchy with M words of fast memory, with different digits stored in different memory words. The considered hybrid algorithms combine the Toom-Cook-k (or Toom-k) fast integer multiplication approach with computational complexity Theta(c(k)n(logk) ((2k-1))), and "standard" integer multiplication algorithms which compute Omega(n(2)) digit multiplications. We present an Omega((n/max{M, n(0)})(logk (2k-1)) (max{1, n(0)/M})(2) M) lower bound for the I/O complexity of a class of "uniform, non-stationary" hybrid algorithms, where n(0) denotes the threshold size of sub-problems which are computed using standard algorithms with algebraic complexity Omega(n(2)). As a special case, our result yields an asymptotically tight Omega(n(2)/M) lower bound for the I/O complexity of any standard integer multiplication algorithm. As some sequential hybrid algorithms from this class exhibit I/O cost within a O(k(2)) multiplicative term of the corresponding lower bounds, the proposed lower bounds are almost asymptotically tight and indeed tight for constant values of k. By extending these results to a distributed memory model with P processors, we obtain both memory-dependent and memory-independent I/O lower bounds for parallel versions of hybrid integer multiplication algorithms. All the lower bounds are derived for the more general class of "non-uniform, non-stationary" hybrid algorithms that allow recursive calls to have a different structure, even when computing sub-problems with the same input size, and to use different versions of Toom-k.

关键词： Integer Multiplication I/O complexity hybrid algorithms Lower Bounds Parallel Model Distributed Memory

来源：评论

学校读者我要写书评

暂无评论

A visual workspace for hybrid multidimensional scaling algorithms

A visual workspace for hybrid multidimensional scaling algor...

引用

9th Annual IEEE Symposium on Information Visualization (INFOVIS 2003)

作者： Ross, G Chalmers, M Univ Glasgow Dept Comp Sci Glasgow G12 8QQ Lanark Scotland

ISBN: (纸本)0780381548

In visualising multidimensional data, it is well known that different types of data require different types of algorithms to process them. Data sets might be distinguished according to volume, variable types and distribution, and each of these characteristics imposes constraints upon the choice of applicable algorithms for their visualisation. Previous work has shown that a hybrid algorithmic approach can be successful in addressing the impact of data volume on the feasibility of multidimensional scaling (MDS). This suggests that hybrid combinations of appropriate algorithms might also successfully address other characteristics of data. This paper presents a system and framework in which a user can easily explore hybrid algorithms and the data flowing through them. Visual programming and a novel algorithmic architecture let the user semi-automatically define data flows and the co-ordination of multiple views.

关键词： data-flow visual programming multidimensional scaling multiple views hybrid algorithms complexity

来源：评论

学校读者我要写书评

暂无评论

Integrating the artificial intelligence and hybrid machine learning algorithms for improving the accuracy of spatial prediction of landslide hazards in Kurseong Himalayan Region

引用

Artificial Intelligence in Geosciences 2022年第1期3卷 14-27页

作者： Anik Saha Sunil Saha Department of Geography University of Gour BangaMaldaIndia

The aim of the current work is to compare susceptibility maps of landslides produced using machine learning techniques *** perception neural nets(MLP),kernel logistic regression(KLR),random forest(RF),and multivariate adaptive regression splines(MARS);novel ensemble approaches ***-Bagging,KLR-Bagging,RFBagging and MARS-Bagging in the Kurseong-Himalayan *** the ensemble models the RF,KLR,MLP and MARS were used as base classifiers,and Bagging was used as meta *** objective of the current work is to introduce and evaluate the effectiveness of the novel KLR-Bagging and MARS-Bagging ensembles in susceptibility to *** 303 landslide locations to calibrate and test the models,an inventory map was *** LCFs were chosen using the Relief-F and multi-collinearity tests for mapping the landslide *** receiver operating characteristic(ROC),precision,accuracy,incorrectly categorized proportion,mean-absolute-error(MAE),and root-mean-square-error(RMSE),the LSMs were subsequently *** different validation results showed RF-Bagging(AUC training 88.69%&testing 92.28%)with ensemble Meta classifier gives better performance than the MLP,KLR,RF,MARS,MLP-Bagging,KLR-Bagging,and MARSBagging based *** model showed that the slope,altitude,rainfall,and geomorphology played the most vital role in landslide occurrence comparing the other *** results will help to reduce the losses caused by the landslides in the Kurseong and in other areas where geo-environmental and geological conditions more or less similar.

关键词： Multilayer perception Kernel logistic regression Random forest Multivariate adaptive regression splines hybrid algorithms

来源：评论

学校读者我要写书评

暂无评论

Harnessing hybrid Random Search algorithms for Intelligent State Control in Technological Processes

Harnessing Hybrid Random Search Algorithms for Intelligent S...

引用

International Conference on Intelligent and Fuzzy Systems (INFUS)

作者： Musaev, A. A. Grigoriev, D. A. ITMO Univ St Petersburg Russia St Petersburg State Univ SPBU Ctr Econometr & Business Analyt CEBA St Petersburg Russia

ISBN: (纸本)9783031671913;9783031671920

This article presents a research focused on improving the control of stochastic search procedures within an e-neighborhood surrounding current monitoring outcomes of control parameters in technological processes. The research aimed to enhance the effectiveness of control measures through the utilization of state-of-the-art Random Search (RS) technology. A mathematical structure was established to define an e-neighborhood for manipulating parameters and setting boundaries for the search space. Various methods were explored for selecting manipulation parameters using operator-driven processes via Human-Machine Interface (HMI) tools. The RS-Control Module's functional structure accounted for the dynamics of controlled parameter evolution using a sliding observation window. The RS-Optimization Module's software implementation allowed for forecasting output parameters and assessing forecast accuracy using quality indicators. The implementation of the main program provided a user-friendly interface for adjusting process parameters, optimizing criteria, and monitoring control based on RS forecasts. The research demonstrated the effectiveness of the proposed approach in improving output and technological parameters in industrial processes.

关键词： Stationarity violation Random Search algorithms hybrid algorithms Predictive algorithms

来源：评论

学校读者我要写书评

暂无评论

Problems and features of evolutionary algorithms to build hybrid training methods for recurrent neural networks

Problems and features of evolutionary algorithms to build hy...

引用

9th International Conference on Enterprise Information Systems (ICEIS 2007)

作者： Cuellar, M. P. Delgado, M. Pegalajar, M. C. Univ Granada Dept Comp Sci & Artificial Intelligence Granada Spain

ISBN: (纸本)9789728865894

Dynamical recurrent neural networks are models suitable to solve problems where the input and output data may have dependencies in time, like grammatical inference or time series prediction. However, traditional training algorithms for these networks sometimes provide unsuitable results because of the vanishing gradient problems. This work focuses on hybrid proposals of training algorithms for this type of neural networks. The methods studied are based on the combination of heuristic procedures with gradient-based algorithms. In the experimental section, we show the advantages and disadvantages that we may find when using these training techniques in time series prediction problems, and provide a general discussion about the problems and cases of different hybridations based on genetic evolutionary algorithms.

关键词： recurrent neural network hybrid algorithms time series

来源：评论

学校读者我要写书评

暂无评论

hybrid population-based algorithms for the bi-objective quadratic assignment problem

引用

Journal of Mathematical Modelling and algorithms 2006年第1期5卷 111-137页

作者： López-Ibáñez, Manuel Paquete, Luís Stützle, Thomas Centre for Emergent Computing School of the Built Environment Napier University Edinburgh EH10 5DT 10 Colinton Rd United Kingdom Faculdade de Economia Centro de Sistemas Inteligentes Universidade Do Algarve Faro 8005-139 Portugal Université Libre de Bruxelles Brussels 1050 Avenue Franklin Roosevelt 50 Belgium

We present variants of an ant colony optimization (MO-ACO) algorithm and of an evolutionary algorithm (SPEA2) for tackling multi-objective combinatorial optimization problems hybridized with an iterative improvement algorithm and the robust tabu search algorithm. The performance of the resulting hybrid stochastic local search (SLS) algorithms is experimentally investigated for the bi-objective quadratic assignment problem (bQAP) and compared against repeated applications of the underlying local search algorithms for several scalarizations. The experiments consider structured and unstructured bQAP instances with various degrees of correlation between the flow matrices. We do a systematic experimental analysis of the algorithms using outperformance relations and the attainment functions methodology to asses differences in the performance of the algorithms. The experimental results show the usefulness of the hybrid algorithms if the available computation time is not too limited and identify SPEA2 hybridized with very short tabu search runs as the most promising variant. © Springer 2006.

关键词： Ant colony optimization Evolutionary algorithms hybrid algorithms Multi-objective quadratic assignment problem Stochastic local search Tabu search

来源：评论

学校读者我要写书评

暂无评论

Accelerating the Unacceleratable: hybrid CPU/GPU algorithms for Memory-Bound Database Primitives 15

Accelerating the Unacceleratable: Hybrid CPU/GPU Algorithms ...

引用

15th International Workshop on Data Management on New Hardware (DaMoN)

作者： Gowanlock, Michael Karsin, Ben Fink, Zane Wright, Jordan No Arizona Univ Sch Informat Comp & Cyber Syst Flagstaff AZ 86011 USA Univ Libre Bruxelles Dept Comp Sci Brussels Belgium

ISBN: (纸本)9781450368018

Many database operations have a low compute to memory access ratio. In heterogeneous systems, where a graphics processing unit (GPU) is interconnected via PCIe, the data transfer bottleneck is perceived as insurmountable to achieving performance gains on these memory-bound database primitives. On the other hand, several compute-bound database operations have been shown to achieve significant performance gains using the GPU. This leads to CPU-only memory-bound applications having an increasingly non-negligible impact on database query throughput. In this paper we examine several of these overlooked algorithms, including (i) batched predecessor searches;(ii) multiway merging;and, (iii) partitioning. We examine the performance of parallel CPU-only, GPU-only, and hybrid CPU/GPU approaches, and show that hybrid algorithms achieve respectable performance gains. We develop a model that considers main memory accesses and PCIe data transfers, which are two major bottlenecks for hybrid CPU/GPU algorithms. The model lets us analytically determine how to distribute work between the CPU and GPU to maximize resource utilization while minimizing load imbalance. We show that our model can accurately predict the fraction of work to be sent to each architecture, and consequently, confirms that these overlooked database primitives can be accelerated despite their memory-bound nature.

关键词： GPGPU Heterogeneous Systems hybrid algorithms In-memory Database Memory-Bound algorithms

来源：评论

学校读者我要写书评

暂无评论

A hybrid Algorithm for the Prediction of Computer Vision Syndrome in Health Personnel Based on Trees and Evolutionary algorithms 13th

A Hybrid Algorithm for the Prediction of Computer Vision Syn...

引用

13th International Conference on hybrid Artificial Intelligent Systems (HAIS)

作者： Artime Rios, Eva Maria Sanchez Lasheras, Fernando Suarez Sanchez, Ana Iglesias-Rodriguez, Francisco J. Segui Crespo, Maria del Mar Hosp Univ Cent Asturias Oviedo Spain Univ Oviedo Dept Math Oviedo Spain Univ Oviedo Dept Business Adm Oviedo Spain Univ Alicante Dept Opt Pharmacol & Anat Alicante Spain

ISBN: (纸本)9783319926391;9783319926384

In the last decades, the use of video display terminals in workplaces has become more and more common. Despite their remarkable advantages, they imply a series of risks for the health of the workers, as they can be responsible for ocular and visual disorders. In this research, certain problems associated to prolonged computer use classified under the name of Computer Vision Syndrome are studied with the help of a hybrid algorithm based on regression trees and genetic algorithms. The importance of the different symptoms on the Computer Vision Syndrome is evaluated. Also, the proposed algorithm is tested in order to know its performance as a prediction model that can determine how prone an individual is to suffering from Computer Vision Syndrome.

关键词： hybrid algorithms Genetic algorithms Regression tree Computer vision syndrome

来源：评论

学校读者我要写书评

暂无评论

Proposal of New hybrid Fuzzy Clustering algorithms - Application to Breast Cancer Dataset

Proposal of New Hybrid Fuzzy Clustering Algorithms - Applica...

引用

IEEE Latin American Conference on Computational Intelligence (LA-CCI)

作者： Coutinho, Pedro Henrique S. das Chagas, Thiago P. Univ Estadual Santa Cruz Dept Ciencias Exatas & Tecnol BR-45662900 Ilheus Brazil

ISBN: (纸本)9781538637340

This paper presents new hybrid fuzzy clustering algorithms. The aims of the proposed modifications are to provide robustness for the initial cluster centers using Subtractive clustering and to reduce the number of iterations using the Fuzzy ckMeans center updating strategy. These modifications are applied in the conventional fuzzy clustering algorithms: Fuzzy c-Means, Gustafson-Kessel and Gath-Geva. The proposed methods are applied to Wisconsin Breast Cancer dataset and results compare the proposed algorithms with their conventional forms considering different validity indices and classification accuracy.

关键词： Fuzzy clustering hybrid algorithms Subtractive clustering Breast cancer

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：