Search Results - (( developing models partitioning algorithm ) OR ( java implication based algorithm ))
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An enhanced soft set data reduction using decision partition order technique
Published 2017“…The results show that the decision partition order technique performs up to 50% in parameter reduction, while some algorithms could not obtain any reduction. …”
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Thesis -
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New Structural Evolving Algorithms For Fuzzy Systems
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Thesis -
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An approach to modelling and simulating multithreaded schedulers for divide and conquer problems on multicore architecture / Alaa Mohammed Ali Wadi Al-Obaidi
Published 2016“…The results of simulation models show a high efficiency in dealing with Divide and Conquer algorithms. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Design of a floating point unit for 32-bit 5 stage pipeline processor
Published 2020“…The development project will start by studying the algorithm of addition on floating point numbers. …”
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Final Year Project / Dissertation / Thesis -
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New Evolving Fuzzy System Algorithms Using Dynamic Constraint
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Dynamic area coverage algorithms for static and mobile wireless sensor network environments using voronoi techniques
Published 2011“…This thesis focuses on developing Voronoi Tessellation-based Coverage Optimization Algorithms for Static and Mobile Wireless Sensor Networks, where a large number of static nodes are supported by few mobile nodes in carrying out the sensing task. …”
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Cutpoint determination methods in competing risks subdistribution model
Published 2009“…In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
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Cutpoint determination methods in competing risks subdistribution model
Published 2009“…In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
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Hardware software partitioning of crankshaft function in engine control units using FPGA-based testing
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Automated time series forecasting
Published 2011“…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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Monograph -
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REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
Published 2011“…The performance of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. …”
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An Accurate and Efficient Shooting-and-bouncing-polygon Ray Tracer For Radio Propagation Modelling
Published 2019“…We have described the associated problems and proposed an algorithm to perform the transformation or projection.Thirdly, we have proposed a new spatial partitioning scheme to be used with the SBP ray tracer. …”
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Final Year Project / Dissertation / Thesis -
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Predictive Framework for Imbalance Dataset
Published 2012“…Properties of the proposed framework include; developing an approach to correlate materials defects, developing an approach to represent data attributes features, analyzing various ratio and types of data re-sampling, analyzing the impact of data dimension reduction for various data size, and partitioning data size and algorithmic schemes against the prediction performance. …”
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Shot boundary detection based on orthogonal polynomial
Published 2019“…The design of SBD algorithms developed from simple feature comparison to rigorous probabilistic and using of complex models. …”
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Hypertension Prediction in Adolescents Using Anthropometric Measurements: Do Machine Learning Models Perform Equally Well?
Published 2022“…The use of anthropometric measurements in machine learning algorithms for hypertension prediction enables the development of simple, non-invasive prediction models. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…The developed optimization model could be used as a decision making support tool to evaluate and select various alternative renewable energy resources and to determine the optimal locations for developing these resources. …”
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