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检索条件"主题词=software algorithms"

共 12322 条记录，以下是261-270 订阅

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Alternative Quadrant Representations with Morton Index and AVX2 Vectorization for AMR algorithms within the p4est software Library

Alternative Quadrant Representations with Morton Index and A...

引用

IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Mikhail Kirilin Carsten Burstedde Institute for Numerical Simulation University of Bonn Bonn Germany

ISBN: (数字)9798350364606

ISBN: (纸本)9798350364613

We present a technical enhancement within the p4est software for parallel adaptive mesh refinement. In p4est mesh primitives are stored as octants in three and quadrants in two dimensions. While, classically, they are encoded by the native approach using its spatial coordinates and refinement level, any other mathematically equivalent encoding might be used instead. Recognizing this, we add two alternative representations to the classical, explicit version, based on a long monotonic index and 128-bit AVX quad integers, respectively. The first one requires changes in logic for low-level quadrant manipulating algorithms, while the other exploits data level parallelism and requires algorithms to be adapted to SIMD instructions. The resultant algorithms and data structures lead to higher performance and lesser memory usage in comparison with the standard baseline. We benchmark selected algorithms on a cluster with two Intel(R) Xeon(R) Gold 6130 Skylake family CPUs per node, which provides support for AVX2 extensions, 192 GB RAM per node, and up to 512 computational cores in total.

关键词： Three-dimensional displays software algorithms Memory management Random access memory Clustering algorithms Prediction algorithms software

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Application of Data Mining algorithms in Financial Analysis software

Application of Data Mining Algorithms in Financial Analysis ...

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Communications and Information Technologies (GCCIT), Global Conference on

作者： Fang Xiao School of Communication And Management China

ISBN: (数字)9798350388916

ISBN: (纸本)9798350388923

Risk management plays an important role in the application of financial analysis software, but there is the problem of inaccurate management positioning. Traditional iterative algorithms cannot solve the risk management problems in the application of financial analysis software, and the effect is not satisfactory. Therefore, this paper proposes the application of financial analysis software based on data mining algorithm and analyzes the application in financial analysis software. Firstly, the statistical set theory is used to locate the influencing factors, and the indicators is divided according to the requirements of risk management to reduce the interference factors in risk management. Then, the statistical set theory is used to form a risk management scheme of data mining algorithm, and the risk management results is comprehensively analyzed. The MATLAB simulation results show that under certain evaluation criteria, the data mining algorithm is better than the traditional iterative algorithm in terms of risk management accuracy and risk management influencing factor time.

关键词： Simulation software algorithms Interference Financial management Set theory software Risk management Data mining Iterative methods MATLAB

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Approximation algorithms for software Component Selection Problem

Approximation Algorithms for Software Component Selection Pr...

引用

Asia-Pacific Conference on software Engineering

作者： Nima Haghpanah Shahrouz Moaven Jafar Habibi Mehdi Kargar Soheil Hassas Yeganeh Department of Computer Engineering Sharif University of Technology Tehran Iran

Today's software systems are more frequently composed from preexisting commercial or non-commercial components and connectors. These components provide complex and independent functionality and are engaged in complex interactions. Component-Based software Engineering (CBSE) is concerned with composing, selecting and designing such components. As the popularity of this approach and hence number of commercially available software components grows, selecting a set of components to satisfy a set of requirements while minimizing cost is becoming more difficult. This problem necessitates the design of efficient algorithms to automate component selection for software developing organizations. We address this challenge through analysis of Component Selection, the NP-complete process of selecting a minimal cost set of components to satisfy a set of objectives. Due to the high order of computational complexity of this problem, we examine approximating solutions that make the component selection process practicable. We adapt a greedy approach and a genetic algorithm to approximate this problem. We examined the performance of studied algorithms on a set of selected ActiveX components. Comparing the results of these two algorithms with the choices made by a group of human experts shows that we obtain better results using these approximation algorithms.

关键词： Approximation algorithms software algorithms Costs software systems Connectors software engineering Algorithm design and analysis Computational complexity Genetic algorithms Humans

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Performance Analysis of Machine Learning algorithms Using Bagging Ensemble Technique for software Fault Prediction

Performance Analysis of Machine Learning Algorithms Using Ba...

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International Conference on Information Systems and Computer Networks (ISCON)

作者： Roshan Samantaray Himansu Das School of Computer Engineering KIIT Deemed to be University Bhubaneswar India

software development comes with a lot of challenges. Developers face various issues with performance and bugs. These issues increase with the scale of the project and if fewer individuals work on the development. It has become necessary to fix various bugs during development to ensure better performance and reduce the chances of failure during the deployment of the software. As a result of this, faults in the software must be predicted during the earlier stages of development. This would help in reducing the cost of maintenance of the software post-deployment. Multiple software fault prediction (SFP) approaches have been proposed to tackle this problem. These approaches can be improved by implementing ensemble techniques. In this paper, we study the effect of the bagging technique and how it helps to improve the predictive capability across various datasets. These datasets are provided and made open source by NASA. Decision Tree Classifier (DTC), Logistic Regression (LR), K-Nearest Neighbors (KNN), Gaussian Naive Bayes (GNB), and Support Vector Classifier (SVC) were used as base classifiers for the bagging method. Random forest (RFC) is an ensemble learning algorithm that uses the bagging technique. Based on the outcome of the results, it was concluded that RFC was the best-performing algorithm.

关键词： Machine learning algorithms software algorithms NASA Support vector machine classification Static VAr compensators Gaussian processes Prediction algorithms

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Computational Science and Intelligence Programming in Business with Genetic, Generic algorithms and AI software Products: An Adaptive Algorithmic Approach

Computational Science and Intelligence Programming in Busine...

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International Conference on Computational Science and Computational Intelligence (CSCI)

作者： Anastasia-Dimitra Lipitakis Evangelia A.E.C. Lipitakis Department of Informatics and Telematics Harokopio University Athens Hellas Kent Business School University of Kent Canterbury England

ISBN: (数字)9781728155845

ISBN: (纸本)9781728155852

In this research study the topic of Artificial Intelligence and Business is examined. AI methodologies and their usage in several organizations in various applications concerning staffing, careers etc. and hiring predictions are discussed. The concept of genetic and generic algorithms with their several important aspects are discussed and various related applications in a wide spectrum of topics are presented. Various genetic programming implementations with the corresponding related software products are given and several AI software packages, genetic algorithmic methodologies and related applications are presented.

关键词： Genetic algorithms Genetic programming Sociology Statistics software algorithms Artificial intelligence

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software Modularization by Combining Genetic and Hierarchical algorithms

Software Modularization by Combining Genetic and Hierarchica...

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International Conference on Knowledge-Based Engineering and Innovation (KBEI)

作者： Amir Hossein Farajpour Tabrizi Habib Izadkhah Department of Computer Engineering University College of Daneshvaran Tabriz Iran Department of Computer Science University of Tabriz Tabriz Iran

Modularization is used as one of the stages of reverse engineering to understand a software system. Due to the importance of understanding a software system for development and maintenance, software modularization is considered as one of the challenging tasks and it is important to find a suitable and understandable modularization. The aim of modularization is to partition a software system from the source code into meaningful and comprehensible subsystems (modules). In the literature, the hierarchical and search-based methods are usually used for software modularization. The major advantage of hierarchical methods is that they can show the hierarchical characteristic of a source code and therefore, make the software better and easier to understand. However, the main drawback of these methods is that they are greedy; and since software modularization problem is an NP-Hard problem, are not able to find a proper modularization. In contrast, the search-based methods are able to find a more acceptable modularization; however, the main disadvantage of these methods is that they could not represent the hierarchical characteristic of a source code. In this paper, a combined method (combining hierarchical method with the search-based method) is proposed to use the advantages of both methods. The results on a number of software systems demonstrate that in modularization with the proposed method, not only the quality of modularization is improved over hierarchical methods, but also the hierarchical characteristic make the software structure easy to understand.

关键词： software algorithms software systems Clustering algorithms Genetic algorithms Couplings Search problems

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Performance assessment of baseband algorithms for direct conversion tactical software defined receivers: I/Q imbalance correction, image rejection, DC removal, and channelization

Performance assessment of baseband algorithms for direct con...

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MILCOM, Military Communications Conference

作者： M.K. Nezami Raytheon Company Saint Petersburg FL USA

This paper addresses issues relating to software-defined receivers. Namely radio frequency (RF) to baseband architectures and the signal processing algorithms involved. Several direct conversion receiver architectures are introduced and analyzed for their performance. Issues relating to the quadrature imbalances and DC offset impairments are analyzed and detailed. To estimate and compensate for these impairments, several DSP algorithms are proposed and simulated for use with these receivers.

关键词： Baseband software algorithms Image converters software performance Signal processing algorithms Receivers Radio frequency Computer architecture Performance analysis Digital signal processing

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Improving the Efficiency of software Defined Network through Load Balancing algorithms

Improving the Efficiency of Software Defined Network through...

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Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), International Conference on

作者： B Rukmini Bhat N S Sneha Keerthana Bhat Chaithra C Kamath Chaitha Naik Shri Madhwa Vadiraja Institute of Technology & Management Udupi India

ISBN: (数字)9781665419604

ISBN: (纸本)9781665429986

In this current era, usage of the internet is increasing drastically. Digitization has led to high network traffic which makes the overall management of network highly complex and expensive as traditional networks are non-programmable. As a solution for these issues in traditional networks, software Defined Networking (SDN) has been introduced. SDN decouples the data plane and control plane, thereby making the network programmable. Load balancing in SDN is done to ensure effective management of resources as per client's request. This paper focuses on the effect of Load balancing on SDNs. Here, RTT is calculated for two cases. One, with application of least connection and Dijkstra algorithms and the other, without applying the algorithm. The result is compared to justify the efficiency improvement. We evaluate our system using mininet network emulator and the results demonstrate the feasibility and efficiency of our proposed scheme in terms of delay and overhead.

关键词： software algorithms Telecommunication traffic Load management Real-time systems Servers software defined networking Standards

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A User Evaluation of Process Discovery algorithms in a software Engineering Company

A User Evaluation of Process Discovery Algorithms in a Softw...

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International Conference on Enterprise Distributed Object Computing (EDOC)

作者： Simone Agostinelli Fabrizio Maria Maggi Andrea Marrella Fredrik Milani Sapienza Universita di Roma Rome Italy University of Tartu Tartu Estonia

Process mining methods allow analysts to use logs of historical executions of business processes in order to gain knowledge about the actual behavior of these processes. One of the most widely studied process mining operations is automated process discovery. An event log is taken as input by an automated process discovery method and produces a business process model as output that captures the control-flow relations between tasks that are described by the event log. In this setting, this paper provides a systematic comparative evaluation of existing implementations of automated process discovery methods with domain experts by using a real life event log extracted from an international software engineering company and four quality metrics: understandability, correctness, precision, and usefulness. The evaluation results highlight gaps and unexplored trade-offs in the field and allow researchers to improve the lacks in the automated process discovery methods in terms of usability of process discovery techniques in industry.

关键词： Companies Systematics Tools Complexity theory software algorithms Data mining

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Experimental verification of space-time algorithms using the smart antenna software radio test system (SASRATS) platform

Experimental verification of space-time algorithms using the...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： P.J. Green D.P. Taylor Department of Electrical and Computer Engineering University of Canterbury Christchurch New Zealand

This work covers the experimental verification of 2 space-time (ST) algorithms on the smart antenna software radio test system (SASRATS) platform . This work also covers the concept and architecture of SASRATS, which was designed and developed to facilitate the field testing of ST processing architectures and algorithms. The paper covers the experimental verification of two robust ST algorithms developed by the authors for signal enumeration and channel order estimation. Simulation results are also presented and compared with the experimental results obtained on the SASRATS platform.

关键词： software algorithms software radio software testing System testing Robustness Mathematical model Computer architecture Rats Signal processing Antenna arrays

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