Search
211 articles for “Principal Component”
-
Simultaneous Optimization of MIG Welding Process Parameters Using Taguchi with Principle Component Analysis
Abstract: The aim is to verify the optimum parameters in MIG welding of mild steel for achieving the best result. The three parameters taken for welding are welding current (WC), welding speed (WS) and voltage (V) at three levels. The various parameters which have been used here are modeled by performing experiments in principal component analysis (PCA) based on Taguchi. On applying principle component analysis (PCA),all the input factors are converted …
Published in Journal of Experimental & Applied Mechanics · Vol. 10, Issue 3, 2019 · pp. 13–21 Read article
-
Iris Recognition System Using Principal Component Analysis based Back-Propagation Learning Neural Networks
Abstract: This paper deals with the iris recognition system using Back-Propagation learning neural network algorithm where Principal Component Analysis technique has been used to reduce the dimension of the iris feature vector. Automated iris localization and segmentation methods have applied to effectively isolate the iris region from pupil and sclera. Circular Hogue transform has used to detect the iris/sclera boundary and pupil/iris boundary. To remove the upper and lower eyelids effects …
Published in Current Trends in Information Technology · Vol. 3, Issue 3, 2013 · pp. 5–11 Read article
-
Optimization of Process Parameters of Two Way Abrasive Flow Machining by Grey Relational Analysis Coupled with Principle Component Analysis
Abstract: Now a days as the advancement of technology is increasing rapidly, expectation of human, from industry also increased. To fulfil these expectations new technologies are coming into existence. In this regard unconventional machining processes are playing an important role. Abrasive flow machining is a non-traditional finishing process used for finishing parts with predominantly irregular geometry. In AFM, material removal and surface finish takes place by flowing visco elastic abrasive carrier …
Published in Journal of Experimental & Applied Mechanics · Vol. 6, Issue 2, 2015 · pp. 44–56 Read article
-
Simultaneous Optimization of Multiple Performance Characteristics in MIG Welding for Machining AISI-304 Stainless Steel by Weighted Principle Component Analysis
Abstract: The effect of MIG welding parameters specifically Welding current, Voltage, Gas flow rate and Plate thickness during welding of AISI-304 stainless steel Material on MIG welding machine at different level presents in this work. All the welding parameters are modeled using Taguchi-based Principle Component Analysis (PCA). Principal component is used as multiple responses optimizing technique to drive optimal solution, which gives the overall quality index in experimental process, and finally …
Published in Journal of Experimental & Applied Mechanics · Vol. 9, Issue 3, 2018 · pp. 77–85 Read article
-
Chi-Square Statistic and Principal Component Analysis Based Compressed Feature Selection Approach for Naïve Bayesian Classifier
Abstract: Many of the machine learning algorithms are based on an assumption of attribute independency and often used in domains where the assumption doesn’t hold true. Naïve Bayesian (NB) classifier makes assumption that all the features are conditionally independent given the class labels; In this paper, attribute dependencies were analyzed using Chi-Square test and the Principal Component Analysis (PCA) was carried out on the whole dataset to get a set of …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 2, 2015 · pp. 16–23 Read article
-
Dual Principal Component Analysis in Software Reliability Studies
Abstract: Software usage has been occupying major parts in all the activities of individuals as well as organizations. Expectation of the end users about failure free operations of software is also increasing rapidly. Zhang and Pham defined 32 environmental factors for studying reliability of software and categorized them into five groups. Later Zhu et al. proposed to use information about three principal components extracted from 10 environmental factors only to study …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 41s–46s Read article
-
Multi Objective Optimization in Turning Parameters of Al 6463 using Principal Component Analysis
Abstract: AbstractIn multi objective optimization, weight criterion of each objective is important for producing better and accurate solutions. Now a day, due to the growing requirement of the higher precision apparatus for its useful aspect, machining time (MT) and material removal rate (MRR) of a machined part plays a significant role in the modern manufacturing process. This study focuses on optimizing CNC turning parameters on Al 6463 based on principal component …
Published in Journal of Materials & Metallurgical Engineering · Vol. 7, Issue 2, 2017 · pp. 6–15 Read article
-
Multi-response Optimization of Process Parameter of Spark Erosion Electric Discharge Machining Using Principal Component Analysis Coupled with TOPSIS
Abstract: Electric Discharge Machining (EDM) is a thermo-electric non-traditional machining process in which material removal takes place through the process of controlled spark generation between a pair of electrodes submerged in a dielectric fluid. Due to difficulty in the availability of EDM, it is very complicated to determine optimal process parameters for improving performance. Therefore, optimization of process parameters is an important action in machining, especially for nontraditional machining procedures like …
Published in Journal of Experimental & Applied Mechanics · Vol. 6, Issue 2, 2015 · pp. 70–80 Read article
-
Principal Component Analysis for Outlier Detection
Abstract: Principal Components Analysis (PCA) is one of the well-known and frequently used multivariate exploratory data analyses. PCA is concerned with analyzing and understanding data in high dimensions, that is to say, PCA method analyzes data sets that represent observations which are identified by several dependent variables that are inter-correlated. Multidimensional scaling (MDS) is a technique that makes a map displaying the comparative attitudes of a number of objects or cases, …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 62s–68s Read article
-
Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method
Abstract: This study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. In order to achieve this, we analyzed detailed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various performance indicators. The datasets included comprehensive statistics from multiple matches and tournaments, allowing for an in-depth evaluation of players’ skills and contributions. PCA ranked players according to their participation …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 20–30 Read article
-
Audio-Only Speaker Identification using Principal Component Analysis based Back-Propagation Learning Neural Network in Noisy Environment
Abstract: This paper introduces text dependent speaker identification system on Principal Component Analysis based Back-Propagation learning neural network which deals with detecting a particular speaker from a known populations under noisy environment. For audio pre-processing, ends point detection, silence parts removal, frame segmentation and windowing techniques have been used and wiener filter has been applied to remove the background noise from the audio speech utterances. To reduce the dimension of the …
Published in Current Trends in Signal Processing · Vol. 3, Issue 3, 2013 · pp. 1–10 Read article
-
Financial Forecast: Systematic Analysis Using Principal Component Analysis
Abstract: The most popular technique for data exploration and analysis across all scientific disciplines that can influence the classification model's accuracy is principal component analysis (PCA). In this study, the high dimensionality of the stock market is examined in order to forecast market movements using PCA in conjunction with linear regression. While reducing data redundancy, PCA can aid in enhancing the predictive performance of machine learning techniques. The New York Stock …
Published in E-Commerce for Future & Trends · Vol. 9, Issue 2, 2022 · pp. 18–24 Read article
-
Person Identification Using Iris, Facial Image and Fingerprint with the Combined Algorithm of Principle Component Analysis and Singular Value Decomposition
Abstract: In this research, we consider three most important biometric features such as fingerprint, iris, and facial image to identify a person more precisely. Unimodal biometric system has several problems, such as noisy background data, non-universality and spoof attacks. Multimodal biometric systems can solve these limitations effectively by using two or more individual modalities. This system propose the Multimodal biometric systems on fingerprint, iris and facial image using combined algorithm of …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 1, 2017 · pp. 29–34 Read article
-
ECG De-noising Techniques and Optimal Feature Selection Using Principle Component Analysis
Abstract: AbstractECG (Electrocardiography) is used to record and determine the condition of the heart. This paper provides an overview of various ECG de-noising techniques that are used to eliminate different type of noises; therefore, noise reduction procedure to be performed to eliminate different type of noises such as baseline wander, dc offset and high frequency interference, and then the pre-processed signal is used to extract features from the ECG signal. This …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 5, Issue 1, 2018 · pp. 14–20 Read article
-
Principal Component Analysis Based Dominant Features Selection Method for Speaker Identification
Abstract: Cepstrum based features are mostly used in speaker identification. Mel-frequency cepstrum coefficients (MFCCs) and their statistical properties (skewness, kurtosis and standard deviation) are used in this paper for text-dependent speaker identification. Principal component analysis (PCA) is employed to select the dominant feature vector representing the speaker characteristics. Multi-layer neural network is used as the classification engine. There occurs the inter-speaker variation of speech length uttering the same word. The feature …
Published in Current Trends in Signal Processing · Vol. 1, Issue 1-3, 2025 · pp. 33–45 Read article
-
Principal Component Analysis of Black and Brown Seeded Soybean (Glycine max (L.) Merr.) Genotypes at Jimma and Bonga Southwestern Ethiopia
Abstract: Sixty-four soybean genotypes were evaluated for cluster analysis based on their morphological characters. The field experiment was carried out at Jimma and Bonga in south-western Ethiopia during the main cropping season of 2019. The experimental study was laid with simple lattice design with two replications. Data on 11 quantitative agronomic traits were gathered. For all of the examined variables, analysis of variance revealed substantial to very significant variations among genotypes. …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 12, Issue 2, 2023 · pp. 13–17 Read article
-
Multi-Layer Perceptron Neural Network Based Person Identification Using Appearance Based Facial Feature
Abstract: This paper deals with secure person identification system using Back-Propagation learning neural network algorithm where appearance based facial feature and Principal Component Analysis based dimensionality reduction technique have been used. To extract the appearance based facial features, Viola-Jones method has used as a face detector, Stam’s method of Active Shape Model has applied for detecting the facial edges and image pre-processing method has used for eliminating the background noises. For …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 26–34 Read article
-
Retina Recognition System using PCA-based Discrete Hidden Markov Model
Abstract: In this paper, a unique approach of retina recognition system has been proposed. Principal component analysis based dimensionality reduction technique has been used here and discrete hidden Markov model (DHMM) has been applied to classify the retinal images. The retinal images are taken from DRIVE retina database. Then some image pre-processing techniques such as image scaling, median filtering-based noise reduction and edge-detection techniques have been used to ready the retinal …
Published in Journal Of Network security · Vol. 3, Issue 1, 2015 · pp. 28–32 Read article
-
A Robust Face Recognition Model based on Convolutional Neural Networks
Abstract: From the past several years, face recognition is one of the challenging issues in computer vision, due to three main technical problems in it. 1) Expression problem: in which same person shows more than one expression. 2) Illumination problem: in which face images of the person are strongly corrupted by lightning and 3) poses problem: in which large portion of the face becomes invisible due to occlusion. To this end …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 1–11 Read article
-
Statistical Analysis of Air Pollution and Health: Application to Indian Data
Abstract: Rapid and unplanned urbanization and industrialization have resulted in the distortion of India’s air quality and also have created opportunities as well as problems. The problem of Air pollution is very severe in a majority of Indian cities. In the present study, the level of Air pollution concerning urban and vehicular population is studied. The data collected for the study is from various census reports, Central Pollution Control Boards indiastat.com …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 2, Issue 1-3, 2012 · pp. 102–113 Read article