Search Results - (( quantity prediction using algorithm ) OR ( java implication based algorithm ))
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Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob
Published 2014“…The main purpose of this research to test whether Genetic Algorithm can use to predict future sales and be able generates the graph. …”
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023Conference Paper -
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…Using a proper test-bed, after 10000 run times, we compared our newly proposed algorithm with the basic algorithm in terms of reliability and availability. …”
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Discovering decision algorithm from a distance relay event report
Published 2009“…In this study rough-set-based data mining strategy was formulated to discover distance relay decision algorithm from its resident event report. This derived algorithm, aptly known as relay CD-prediction rules, can later be used as a knowledge base in support of a protection system analysis expert system to predict, validate or even diagnose future unknown relay events. …”
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Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
Published 2016“…In this paper a genetic algorithm based multi-objective optimization approach is applied in order to predict the optimal machining parameters for the end milling process of aluminium alloy 6061 T6 combined with minimum quantity lubrication (MQL) conditions using waterbased TiO2 nanofluid as cutting fluid. …”
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Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining
Published 2019“…The best prediction performance was gained on FT indicator using the M5P algorithm (RRSE = 22.44%). …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm
Published 2023“…On the other hand farming is not viewed as an profitable profession, as the farmers suffers heavy loss due to pests and diseases that affects the quality and quantity of the farm produces. Hence, prediction of plant diseases in early stage using contemporary technologies will help the farmers to take well informed early decisions. …”
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Automatic control of flotation process using computer vision
Published 2015“…The performance of improved marker based watershed algorithm was validated by using several industrial and laboratory froth images. …”
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Predicting wheat yield from 2001 to 2020 in Hebei Province at county and pixel levels based on synthesized time series images of Landsat and MODIS
Published 2024“…The results showed that kernel NDVI (kNDVI) and near-infrared reflectance (NIRv) slightly outperform normalized difference vegetation index (NDVI) in yield prediction. And the regression algorithm had a more prominent effect on yield prediction, while the yield prediction model using Long Short-Term Memory (LSTM) outperformed the yield prediction model using Light Gradient Boosting Machine (LGBM). …”
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Cubature kalman optimizer : A novel metaheuristic algorithm for solving numerical optimization problems
Published 2023“…In control system, the CKF algorithm is used to estimate the true value of a hidden quantity from an observation signal that contain an uncertainty. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In the first phase, we divide the stock data in three different clusters on the basis of product categories and sold quantities i.e. Dead-Stock (DS), Slow-Moving (SM) and Fast- Moving (FM) using K-means algorithm. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In the first phase, we divide the stock data in three different clusters on the basis of product categories and sold quantities i.e. Dead-Stock (DS), Slow-Moving (SM) and Fast- Moving (FM) using K-means algorithm. …”
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Frequent patterns minning of stock data using hybrid clustering association algorithm
Published 2009“…In the first phase, we divide the stock data in three different clusters on the basis of product categories and sold quantities i.e. Dead-Stock (DS), Slow-Moving (SM) and Fast-Moving (FM) using K-means algorithm. …”
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Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari
Published 2021“…Sugeno fuzzy inference system (FIS) algorithm was used to model influent parameter, and the FIS parameters were adjusted by ANFIS, integrated Genetic algorithms, GA-FIS, and integrated particle swarm optimisation, PSO-FIS, algorithms. …”
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Oil palm maturity classifier using spectrometer and machine learning
Published 2021“…The prediction was able to produce 100% accuracies by using Linear and Weighted KNN as classification testing algorithm. …”
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Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia
Published 2024“…Accurate water level prediction for both lake and river is essential for flood warning and freshwater resource management. …”
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