Search Results - (( parameter simulation based algorithm ) OR ( features extraction means algorithm ))*

Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING by MERDEKA, MOHAMMAD GALANG

“…Using a one-well cylindrical synthetic reservoir model, a total of 6084 experimental observations were simulated, each with 28 different features as input parameters. …”
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Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin by Zainal Abidin, Abdul Hakim

“…This research purposed clustering algorithm to improve process extracting feature in images to get meaningful information because it can speed up the time to process of extracting meaningful information in images due to the efficient of the algorithm that has high performance to process the image. …”
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Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali by Mohd Razali, Ainaa Farhanah

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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…The extracted features are then fed into the machine learning algorithm for classification process. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…Euclidean Distance, Pearson Correlation and Matching Matrix were used to measure the performance of the feature extraction and clustering methods. Recognition software achieved 87.14%, EPD algorithm achieved 73.57% and HMT algorithm achieved 74.30%) prediction accuracy with OTs. …”
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FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS by Ahmed A.L., Hassoon N., Hak L.A.L., Edan M., Abed H., Abd S.

“…In this paper, a new hybrid strategy Particle Swarm Optimization (PSO) with Bat Algorithm (BA) is proposed to extract features from fingerprint images. …”

An automated cervical pre-cancerous diagnostic system by Nor Ashidi, Mat-Isa, Mohd Yusoff Mashor, Nor Hayati, Othman

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Fuzzy voice classifier and fuzzy voice pathology identification system by Sathees Kumar, Nataraj, Sazali, Yaacob, Prof. Dr., Ahamad Nazri, Abdullah

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Multi-scene design analysis of integrated energy system based on feature extraction algorithm by Huang, Sihua, Mohd Ali, Noor Azizi, Shaari, Nazlina, Mat Noor, Mohd Sallehuddin

“…Finally, according to the given feature vectors, the feature clustering models of various energy loads are established by using K-means clustering algorithm, and the load forecasting results of multi-energy systems are obtained. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

“…The first-order statistics features are mean, standard deviation and entropy while the features extracted by GLCM are contrast, correlation, energy and homogeneity. …”
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Improved measurement of blood pressure by extraction of characteristic features from the cuff oscillometric waveform by Lim, P.K., Ng, S.C., Jassim, W.A., Redmond, S.J., Zilany, M., Avolio, A., Lim, E., Tan, M.P., Lovell, N.H.

“…Using the sequential forward floating selection (SFFS) approach, we were able to achieve a significant reduction in the mean and standard deviation of differences between the estimated SBP values and the reference scoring (MLR: mean +/- SD = -0.3 +/- 5.8 mmHg; SVR and -0.6 +/- 5.4 mmHg) with only two features, i.e., Ratio(2) and Area(3), as compared to the conventional maximum amplitude algorithm (MAA) method (mean +/- SD = -1.6 +/- 8.6 mmHg). …”
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Automatic keypoints extraction from UAV image with refine and improved scale invariant features transform (RI-SIFT) by Dibs, Hayder, Idrees, Mohammed Oludare, Saeidi, Vahideh, Mansor, Shattri

“…First the RI- SIFT algorithm was used to detect and extract CPs from two overlapping UAV images. …”
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Optimised content-social based features for fake news detection in social media using text clustering approach by Yahya, Adnan Hussein Ali

“…In addition, this thesis tackles the feature selection problem by designing a novel wrapper feature selection method based on the Hybrid Flower Pollination Algorithm (HFPA). …”
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A robust technique of brain MRI classification using color features and k-nearest neighbor algorithm by Fayaz, Muhammad, Shah, Abdul Salam, Wahid, Fazli, Shah, Asadullah

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Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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A study on the application of discrete curvature feature extraction and optimization algorithms to battery health estimation by Goh, Hui Hwang, An, Zhen, Zhang, Dongdong, Dai, Wei, Kurniawan, Tonni Agustiono, Goh, Kai Chen

“…The error evaluation metrics used are mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE). …”
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Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. …”
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