Search Results - (( java implication based algorithm ) OR ( frequency identification learning algorithm ))

Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification by Hakim, S.J.S., Abdul Razak, H.

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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm by Abdulwahid S., Mahmoud M.A., Abdulwahid N.

“…Classification (of information); Data mining; Digital forensics; Forestry; Learning algorithms; Loudspeakers; Motion compensation; Nearest neighbor search; Speech recognition; Trees (mathematics); K-near neighbor; Logistic model tree; Logistics model; Mel frequency cepstral co-efficient; Mel frequency cepstral coefficient; Mel-frequency cepstral coefficients; Mining classification; Model trees; Nearest-neighbour; Speaker identification systems; Authentication…”

Development of damage identification scheme using de-noised modal frequency response function data with artificial neural network / Mohamad Izzudin Hussein Shah by Mohamad Izzudin , Hussein Shah

“…Past researches used natural frequency, mode shapes and damping ratio for their damage identification scheme. …”
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Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches by Aman, M., Said, A.M., Kadir, S.J.A., Ullah, I.

“…The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. …”
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Key concept identification: A comprehensive analysis of frequency and topical graph-based approaches by Aman, M., Said, A.M., Kadir, S.J.A., Ullah, I.

“…The objective of the study presented in this paper is to perform a comprehensive empirical analysis of selected frequency and topical graph-based algorithms for key concept extraction on three different datasets, to identify the major sources of error in these approaches. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Damage identification using experimental modal analysis and adaptive neuro-fuzzy interface system (ANFIS) by Hakim, S.J.S., Razak, H.A.

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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad by Mehdi , Jahanirad

“…Both models optimize acoustic features for source mobile device identification based on near-silent segments. The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
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Speaker identification through feature fusion based deep learning / Rashid Jahangir by Rashid , Jahangir

“…In addition, DNN obtained better classification results compared with the other five machine learning algorithms that were recently utilised in speaker recognition. …”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…Hence, an automated process is required for such identification. The proposed approach in this work tends to tackle the multiple EEG channels problem by segmenting the EEG signals in the frequency domain based on changing spikes rather than the traditional time based windowing approach. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Development of Quran reciter identification system using MFCC and neural network by Asda, Tayseer Mohammed Hasan, Gunawan, Teddy Surya, Kartiwi, Mira, Mansor, Hasmah

“…The feature vector will be fed into neural network back propagation learning algorithm for training and identification processes of different speakers. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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Linear Discriminate Analysis And K-Nearest Neighbor Based Diagnostic Analytic Of Harmonic Source Identification by Jopri, Mohd Hatta, Abdullah, Abdul Rahim, Manap, Mustafa, Nor Shah, Mohd Badril, Sutikno, Tole, Too, Jing Wei

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A novel scheme for spectrum prediction in cognitive radio networks / Mehdi Askari and Rezvan Dastanian by Askari, Mehdi, Dastanian, Rezvan

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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…This is the similar case for radio-frequency identification (RFID) pallet level signal as the accuracy of determining the position for specific location either on the level or stacked in the same direction are read uniformly. …”
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Faulty classification system for VTOL UAV acoustic signal using machine learning by Makhtar, Siti Noormiza, Mohd Sani, Fareisya Zulaikha, Nor, Elya Mohd, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad

“…The GUI, designed, enables the identification of different propeller conditions based on time-domain and frequency-domain acoustical features. …”
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Addressing imbalanced EEG data for improved microsleep detection: An ADASYN, FFT and LDA-based approach by Hasan, Md Mahmudul, Khandaker, Sayma, Norizam, Sulaiman, Hossain, Mirza Mahfuj, Islam, Ashraful

“…This paper introduces a novel approach to detecting driver microsleep by leveraging EEG signals and advanced machine learning techniques. The methodology begins with preprocessing raw EEG data to improve quality and balance, utilizing the ADASYN algorithm to address dataset imbalances. …”
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