linear prediction-based approach
On the Additive and Dominant Variance and Covariance of Individuals Within the Genomic Selection Scope
... ABSTRACT Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or “breeding” values of individuals are generated by substitution effects, which involve both ...
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Wide-Band Audio Coding Based on Frequency-Domain Linear Prediction
... Inertia of the human vocal tract organs makes the mod- ulations in the speech signal vary gradually. While short- term predictability within time spans of 10–20 ms and AR modeling of the signal have been used e ff ...
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American Journal of Medical and Biological Research
... immunoinformatic approach to predict highly conserved epitopes against glycoprotein receptor" Gn and Gc" of M protein, that can mediate immune response which can use later to produce a new vaccine that ...
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The implementation of Joint QRS Detection and Data Compression Scheme for Web Based High Accuracy ECG Detection and Healthcare System
... joint approach for QRS detection and lossless data compression (JQDC) will result in lower overall system ...is based on an adaptive linear data prediction scheme which achieves high ...
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Prediction of Sewer Pipe Main Condition Using the Linear Regression Approach
... This paper develops a model to predict the condition of sewer mains. Based on the available data, it shows that among all available variables, the pipe age is the most significant factor. The pipe installation ...
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Application of Multiple Linear Regression Technique to Predict Noise Pollution Levels and Their Spatial Patterns in the Tarkwa Mining Community of Ghana
... LUR based on the MLR could be used for noise prediction of an area with an accuracy of ...is based on the R of ...same approach for the model ...
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Epileptic Seizure Prediction Based On Features Extracted Using Wavelet Decomposition And Linear Prediction Filter
... (LP) linear prediction bias specifies the input and offset periods of the EEG ...updated linear predictor ...Wavelet approach for extract signals features and LightGBM purpose of ...changed ...
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A New Approach to Linear Filtering and Prediction Problems 1
... (5) Optimal Estimates and Orthogonal Projections. The Wiener problem is approached from the point of view of condi- tional distributions and expectations. In this way, basic facts of the Wiener theory are quickly ...
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A Machine Learning Approach for Annual Rainfall Prediction Using Linear Regression Model
... statistical approach to find the relationship between ...event based on the relationship between variables obtained from the ...data-set. Linear regression is one type regression used in Machine ...
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A Hybrid Short-term Traffic Flow Forecasting Method Based on Neural Networks Combined with K-Nearest Neighbor
... dynamic linear model was presented to predict online short-term travel time and investigate the uncertainty of travel time prediction ...nonparametric approach, a hybrid model of a chaos-wavelet ...
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In-silico prediction and observations of nuclear matrix attachment
... motif based supervised machine learning to develop a MAR classification ...a linear discriminant ...The Linear Discriminant Analysis (LDA) based classification was then derived on the basis of ...
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Evaluation of Two Noise Level Prediction Models: Multiple Linear Regression and a Hybrid Approach
... levels based on predictor variables ...levels prediction, LUR modelling has been least ...multiple linear regression ...MLR approach in the noise prediction field, the analytical ...
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A Semi-Supervised Learning Approach for Tackling Twitter Spam Drift
... learning approach (SSLA) has been proposed to tackle this. The new approach uses the unlabeled data to learn the structure of the ...proposed approach and the results show that the proposed SSLA can ...
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Entropy-based approach to missing-links prediction
... links prediction problem can be stated by asking the following question: given a snapshot of a network, can the next most-likely links to be established be predicted? Such an issue is relevant in many research ...
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A knowledge-based approach to protein structure prediction
... Chapter 2 describes the details of our investigations performed to check the fold-discriminatory potentials of various sequence- and structure-based features and develop a new SVM-based method for protein ...
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Los Angeles And Micro-Deval Abrasion Values Estimation For Gneiss And Granite Using ANFIS Approach
... ANFIS approach and the MLR method are used to predict the mechanical properties of rocks including the Los Angeles and Micro Deval from the depths that represent the models input ...
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Argument Mining with Structured SVMs and RNNs
... Our factor graph formulation draws from ideas previously used independently in parsing and ar- gument mining. In particular, maximum spanning tree (MST) methods for arc-factored dependency parsing have been successfully ...
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Drug-Target Interaction Networks Prediction Using Short-linear Motifs
... Support vector machine (SVM) is a supervised learning method. The aim of SVM is to separate the training data by a hyperplane with the largest margin. It uses the concept of kernel instead of mapping data into a higher ...
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A SEMI-SUPERVISED LEARNING APPROACH FOR TACKLING TWITTER SPAM DRIFT
... In this paper, the Twitter Spam Drift problem is studied, and a new idea called a semi- supervised learning approach (SSLA) is proposed. The aim of SSLA is to tackle the Twitter Spam drift by using a ...
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A Referral-Based QoS Prediction Approach for Service- Based Systems
... user based on a database of user votes collected from a sample or population of other user databases ...QoS prediction do not concern how to improve the prediction accuracy with ma trix ...
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