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检索条件"主题词=Software algorithms"

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Stock Price Prediction based on Optimized Attribute and Cascaded Machine Learning Algorithm

Stock Price Prediction based on Optimized Attribute and Casc...

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Advances in Technology, Management & Education (ICATME), International Conference on

作者： Ritesh Kumar Yadav M. Sivakkumar SRK University Bhopal India

ISBN: (纸本)9781728185873

The wealth of currency and nation depends on the growth of the stock market. The prediction of stock price varies according to their parameters such as open price, close price and strike price. The variation of parameters creates an unstable and volatile situation for the stock market. The unstable nature of stock market diverts customers for the investments. In this paper proposed cascaded machine learning algorithm for the stock price prediction. The cascaded machine learning algorithm work with an optimized variance of stock parameters. The process of parameters optimization achieves by particle swarm optimization. The particle swarm optimization is a memory-based and iterative process. The proposed algorithm implemented in MATLAB software and tested with NSE data of different banks such as HDFC, IDBI and AXIS bank.

关键词： Machine learning algorithms software algorithms Education Prediction algorithms software Stock markets Particle swarm optimization

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Design of adaptive compliance control algorithm for upper limb exoskeleton rehabilitation robot

Design of adaptive compliance control algorithm for upper li...

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Chinese Automation Congress (CAC)

作者： Xiaoqing Yuan Tong Zhou Junjie Ji Yuxuan Liu Wendong Wang Fangfang Yue School of Mechanical Engineering Northwestern Polytechnical University Xi’an China

ISBN: (纸本)9781665426480

In order to improve the compliance and accuracy of upper limb exoskeleton rehabilitation robot system, this paper proposes an algorithm of adaptive compliance control combining admittance control and adaptive global fast terminal sliding mode control(AGFTSMC). Firstly, The exoskeleton platform and the control system consisting of the hardware system and software system are introduced. Secondly, The dynamic model and admittance control model of the robot system is established, and the adaptive global fast terminal sliding mode controller is designed. Thirdly, The stability of the system is proved by Lyapunov theory. Finally, the experiments of both passive mode and active mode are designed. The variation characteristics of trajectory tracking deviations, human-computer interaction forces and dynamic parameter estimation are compared and analyzed. The experimental results verify the effectiveness of the adaptive compliance control algorithm.

关键词： Adaptation models Trajectory tracking Heuristic algorithms Exoskeletons software algorithms Rehabilitation robotics software systems

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Hybrid Renewable Energy Resources Utilizing Hybrid PSO and Cuckoo Search Algorithm

Hybrid Renewable Energy Resources Utilizing Hybrid PSO and C...

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International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)

作者： Riah Ann Dr. Fermin-Cayanan Gorgonio C. Vallestero Ronan Cadmiel C. Castro Mark Adrian R. Lunaria School of Graduate Studies Mapua University City of Manila Philippines Bulacan State University City of Malolos Philippines

ISBN: (纸本)9781665401685

Renewable Energy Sources (RES) are the catalysts for climate change for these environmental challenges. From the Philippine Development Plan from 2017-2022, sustainable development supports required massive investment and fast track to improve power generation using renewable energy sources. The system’s reliability is still a challenge due to its intermittent supply of energy dependence on nature. Hybrid Renewable Energy System (HRES) is widely known today to ease effect and balance energy supply. HRES requires a wide selection of techniques to be used to satisfy the demand of a given grid. A recent study was conducted calculating the values of Levelized Cost of Energy (LCOE) using optimization technique; result yields with LCOE and LPSP higher than the current values. This study developed software for Hybrid Renewable Energy Systems in Pamarawan Island that will reduce the Levelized Cost of Energy using Hybrid PSO and Cuckoo Search Algorithm. The result appears that the HPSOCS Algorithm gives an optimized solution that leads to a value of LCOE that is within the acceptable range of the current actual value. For the twenty independent runs of the program, the average value of LCOE is 0. 1508 ${\$}$/kWh, and LPSP is 0.1096 or 10.96%. The researcher assessed the level of significance of the hypothesis using a right-tailed test for the values of LCOE. In all instances, all the observed values of LCOE using Hybrid PSOCS are lower than those of LCOE using HPSOGSA. This means that the Hybrid PSOCS yields LCOE significantly better than HPSOGSA, with a 39% relative difference at a 5% significance level. Thus, the algorithm used has an excellent performance in the optimization method of HRES. Also, the HRES software calculator can be used in sizing HRES in different locations in need of sustainable energy sources.

关键词： Renewable energy sources Costs Calculators software algorithms Optimization methods Search problems software

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An Automated Framework for Generating Synthetic Point Clouds from as-Built BIM with Semantic Annotation for Scan-to-BIM

An Automated Framework for Generating Synthetic Point Clouds...

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Simulation Winter Conference

作者： Jong Won Ma Bing Han Fernanda Leite The University of Texas at Austin Austin TX USA

ISBN: (纸本)9781665433129

Data scarcity is a major constraint which hinders Scan-to-BIM's generalizability in unseen environments. Manual data collection is not only time-consuming and laborious but especially achieving the 3D point clouds is in general very limited due to indoor environment characteristics. In addition, ground-truth information needs to be attached for the effective utilization of the achieved dataset which also requires considerable time and effort. To resolve these issues, this paper presents an automated framework which integrates the process of generating synthetic point clouds and semantic annotation from as-built BIMs. A procedure is demonstrated using commercially available software systems. The viability of the synthetic point clouds is investigated using a deep learning semantic segmentation algorithm by comparing its performance with real-world point clouds. Our proposed framework can potentially provide an opportunity to replace real-world data collection through the transformation of existing as-built BIMs into synthetic 3D point clouds.

关键词： Point cloud compression Deep learning Visualization Three-dimensional displays Annotations Semantics software algorithms

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Area efficient VLSI architecture for reversible radix_2 FFT algorithm

Area efficient VLSI architecture for reversible radix_2 FFT ...

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Syeda Farhat Sultana Basavarja Patil VTU Centre for PG Studies Kalaburagi India

ISBN: (数字)9781728185194

ISBN: (纸本)9781728185200

In this work, we propose a new way of implementing Fast Fourier transform multiplier. Previous approaches achieve FFTs with a unity gain using a complex multiplier or a non-unity gain factor. The IEEE 754 format is used for a floating-point number representation. This project proposes an effective float reconstruction scheme that showed greater delay and area implementation. A community of Karatsuba and Urdhva-Tiryagbhyam algorithms are used to implement a binary multiplier. The algorithms are implemented by Verilog (HDL) and are targeted to the Xilinx ISE simulator for FPGA Spartan-3E board. This decreases the FFT architecture and design computing resources.

关键词： Computational modeling software algorithms Computer architecture Very large scale integration software Delays Hardware design languages

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Recurrent Neural Networks algorithms and applications

Recurrent Neural Networks algorithms and applications

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Big Data & Artificial Intelligence & software Engineering (ICBASE), International Conference on

作者： Yuexing Chen Jiarun Li Rutgers Business School The State University of New Jersey New Brunswick New Jersey United Stated School of Beijing Institute of Petrochemical Technology Beijing China

ISBN: (纸本)9781665427104

Since recurrent neural networks (RNNs) were firstly proposed, it is widely used, and many extended RNNs algorithms have been developed, which achieve good results in many application fields. To report the latest research results of RNNs and help researchers quickly understand the latest progress of RNNs algorithm. In this research, we briefly introduce the basic principle of RNN, review more than 20 papers about RNNs and summarize the previous work. Then, we make qualitative and quantitative analyses on four representative algorithms (CNN-RNN, ResNet-110, ResNet-164, and ResNet-1001). Among them, the model of CNN-RNN obtains the best performance on the CIFAR-100 dataset with standard data augmentation. Finally, we discuss the future development trend of RNNs.

关键词： Recurrent neural networks Statistical analysis software algorithms Diversity reception Prediction algorithms Market research Data models

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SHA-3-LPHP: Hardware Acceleration of SHA-3 for Low-Power High-Performance Systems

SHA-3-LPHP: Hardware Acceleration of SHA-3 for Low-Power Hig...

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IEEE International Conference on software Reliability Engineering Workshops (ISSRE Wksp)

作者： Yuta Akiya Kyle Thomas Le Megan Luong Justin C Wilson Anas Salah Eddin Valerio Formicola Mohamed El-Hadedy California State Polytechnic University Pomona United-States Air Force Academy RecoIoT

ISBN: (纸本)9781665426046

In the last decade, the world transitioned from using Secure Hash Algorithm 1 (SHA-1) to Secure Hash Algorithm 2 (SHA-2) due to the flaws in SHA-1. However, SHA-2 still uses a similar internal structure with the same mathematical flaws as its predecessor. Safety in SHA-2 is attributed to the increased length of its output compared to SHA-1. Since then, a new hashing algorithm, SHA-3 has been introduced, which does not share the same flaws as its other family members. However, the transition to SHA-3 has not been complete due to lack of software and hardware support for SHA-3 as well as performance issues. The performance limitation, however, is only present in software implementations. In this paper, we propose a new implementation of SHA-3 based on FPGA hardware (SHA-3-LPHP), to be integrated in the architecture of low-power devices. SHA-3-LPHP achieves three orders magnitude improvement in execution time as compared to full software implementations, furthermore, requiring less energy, hence making it an excellent candidate for low-power and high-performance systems.

关键词： Performance evaluation Microprocessors System performance software algorithms software software reliability Safety

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Automated Synthetic Aperture Sonar Image Segmentation using Spatially Coherent Clustering

Automated Synthetic Aperture Sonar Image Segmentation using ...

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OCEANS

作者： Shannon-Morgan Steele Jillian Ejdrygiewicz Jeremy Dillon Kraken Robotic Systems Inc Dartmouth Canada

ISBN: (纸本)9781665427883

Seabed image segmentation is an important product for a variety of fields, including, habitat mapping, geological surveys, mine counter measures, and naval route planning. Developing a clustering algorithm that can both accurately segment high resolution imagery and generalize well over large areas is challenging. In this paper we will evaluate the performance of a new unsupervised image segmentation algorithm. The method utilizes imagery derived features (intensity and texture) to identify clusters (different seabed types) in feature space while also encouraging local homogeneity. In this paper we will demonstrate how our spatially coherent k-means clustering algorithm can efficiently and accurately segment Synthetic Aperture Sonar (SAS) images. Our experiments show that our spatially coherent clustering algorithm can increase segmentation accuracy up to 15 and 20 percent relative to OpenCV k-means and ArcGIS Pro ISO clustering, respectively.

关键词： Image segmentation software algorithms Spatial coherence Clustering algorithms Cost function Real-time systems Planning

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Petri net implementation in programmable logic controllers: methodology for development and validation

Petri net implementation in programmable logic controllers: ...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Igor Azkarate Fernández Juan Carlos Mugarza Cortabarría Luka Eciolaza Echeverría Mondragon Unibertsitatea Arrasate-Mondragón Spain

ISBN: (数字)9781728180533

ISBN: (纸本)9781728180540

Lead times are key to good market positioning of providers of automated solutions based on a programmable logic controller (PLC). Testing control software against a digital twin (DT) of the process, any programming errors that may have incurred are detected before commissioning, which reduces project duration. This work raises the possibility of reducing that probability of error when programming discrete event dynamic systems (DEDS), by implementing a Petri net (PN) managing algorithm. A framework is presented which combines the use of this algorithm, by means of pre-incidence and post-incidence matrices and initial marking vector of a net, with code validation through emulation. A use case is brought forward in which the control program of a sequential process with parallel operations is implemented, with both virtual (VC) and real commissioning.

关键词： Heuristic algorithms Buffer storage software algorithms Petri nets Process control Programming software

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High Performance Uncertainty Quantification with Parallelized Multilevel Markov Chain Monte Carlo

High Performance Uncertainty Quantification with Parallelize...

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Supercomputing Conference

作者： Linus Seelinger Anne Reinarz Leonhard Rannabauer Michael Bader Peter Bastian Robert Scheichl Institute for Scientific Computing Heidelberg University Heidelberg Germany Department of Computer Science Durham University Durham United Kingdom Department of Informatics Technical University of Munich Garching Germany Institute for Applied Mathematics Heidelberg University Heidelberg Germany

ISBN: (数字)9781450384421

ISBN: (纸本)9781665483902

Numerical models of complex real-world phenomena often necessitate High Performance Computing (HPC). Uncertainties increase problem dimensionality further and pose even greater challenges. We present a parallelization strategy for multilevel Markov chain Monte Carlo, a state-of-the-art, algorithmically scalable Uncertainty Quantification (UQ) algorithm for Bayesian inverse problems, and a new software framework allowing for large-scale parallelism across forward model evaluations and the UQ algorithms themselves. The main scalability challenge presents itself in the form of strong data dependencies introduced by the MLMCMC method, prohibiting trivial parallelization. Our software is released as part of the modular and open-source MIT Uncertainty Quantification Library (MUQ), and can easily be coupled with arbitrary user codes. We demonstrate it using the Distributed and Unified Numerics Environment (DUNE) and the ExaHyPE Engine. The latter provides a realistic, large-scale tsunami model in which we identify the source of a tsunami from buoy-elevation data.

关键词： Uncertainty Monte Carlo methods Inverse problems Computational modeling High performance computing software algorithms Markov processes

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