Search Results - (( data interpolation method algorithm ) OR ( data classification using algorithm ))

Evaluation of land use land cover changes impacts on water quality at Nerus River using geospatial techniques / Noor Azzatul Najwa Azman by Najwa Azman, Noor Azzatul

“…The method that used to do the classification for each year is supervised classification. …”
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Optimal search algorithm in a big database using interpolation–extrapolation method by Kabir, M. Nomani, Alginahi, Yasser M., Ali, J., Abdel-Raheem, E.

“…Search using traditional binary-search algorithm can be accelerated by employing an interpolation search technique when the data is regularly distributed. …”
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Numerical Integration And Data Reduction For Application In Photometry by Chew, Tong Fatt

“…In this thesis, an algorithm based on a local interpolation scheme called the Average Angle Method was developed for numerical integration and data reduction of photometric data, and in general, for any data set sharing similar characteristics as the luminous intensity data The new interpolation scheme interpolates discrete data with piecewise cubic polynomials having a CI continuity in the interior. knots. …”
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Development of android application for peninsular Malaysia GEOID height calculator / Mohamad Nazir Md Nazri by Md Nazri, Mohamad Nazir

“…This analysis is done to verify the algorithm of interpolation method and to find the best interpolation method for implement in the developed android application. …”
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Exponential Parameterized Cubic B-Spline Curves And Surfaces by Ammad, Muhammad

“…In developing B-spline curve interpolation method, an algorithm is presented for interpolating data points. …”
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Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

“…One method of overcoming this d1ficulty is by incorporating the spline interpolation algorithm into the nonlinear preprocessing procedure. …”
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An efficient method of biometric matching using interpolated ECG data by Sidek, Khairul Azami, Sufi, Fahim, Khalil, Ibrahim, Al-Shammary, Dhiah

“…Results of experiments confirmed that the template matching using interpolation method achieved better accuracy (up to 4.46%) than the existing method without interpolation when using ECG data with lower sampling rate.…”
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Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data by Jayapal V., Zain A.F.M.

“…Normalized RMSE, RMSE and relative correction are computed for both methods to evaluate the capability of NN to interpolate and extrapolate the missing data. …”

Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data by Jayapal, V, Zain, AFM

Shallow-water mapping at Pantai Tok Jembal, Terengganu, Malaysia, using Lansat 8 (OLI) / Nur Syahirah Hashim by Hashim, Nur Syahirah

“…Next, there are three research objectives guideline in this study: i) to identify the best empirical-based method for Satellite-Derived Bathymetry, ii) to evaluate the spatial interpolation technique for generating a calibration dataset and iii) to evaluate the accuracy of Satellite-Derived Bathymetry using the selected empirical-based method and spatial interpolation technique. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…Since the 1960s, many algorithms for data classification have been proposed. …”
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New Curve Fitting Method for Petroleum Engineering Applications by Mohd Rosli, Muhammad Aizuddin

“…Unsuitable type of curve fitting may destroy the original feature of the data. This research is about the invention of new curve fitting method that combined two interpolation method which are Cubic Spline and Piecewise Cubic Hermite Interpolation Polynomial (PCHIP) with the reduction of data method. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

“…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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Development of classification algorithms of human gait by Koh, Chee Hong

“…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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