Search
416 articles for “neural network method”
-
Using Neural Network Method to Construct 3H Content Model
Abstract: This paper proposes a 3H (hero, hub, and hygiene) content model by neural network method to predict the conversion rate of audiences between each of the three layers. The empirical data is collected from a brand of beauty groceries store. There are134,569 audiences who subscribe to this brand’s Youtube channel over one year are involved to make parameters estimation, weight value of each attribute in each content, and calculate the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 39–45 Read article
-
Optimization Study by Response Surface Methodology and Artificial Neural Network on the Culture Parameters of Citric Acid Bioproduction from Sweet Potato Peels
Abstract: In the cause of this research work, two steps enzymatic hydrolysis of sweet potato peel was carried out respectively. The effect of α-amylase dose, reaction time, and reaction temperature and biomass weight on glucose concentration was investigated carefully. The response surface methodology (REM) predicted the highest reducing sugar concentration at liquefaction to be 74 g/L, at the following optimized conditions; temperature of 45°C, α-amylase dose 0.7 %v/v, biomass weight 22.345 …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 9, Issue 1, 2022 · pp. 30–38 Read article
-
Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
-
Multispectral Image Denoising using Bi-Directional Recurrent Neural Network with DPCA Algorithm
Abstract: In practices, a Multispectral Images (MSI) image is always prone to corruption by various sources of noises while procuring the images. In this paper we implemented Decomposable Pixel Component Analysis (DPCA) algorithm with recurrent neural network (RNN) which effectively denoised the MSI images. The RNN enables shrinkage of non-reusable data points during DPCA execution and aid it to effectively transform spatial coordinate in a logical manner and reduces the time …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 25–30 Read article
-
An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing Read article
-
An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
-
Predictive Modeling System for Automated Skin Lesion Classification Using Deep Neural Networks and Voting Ensembles
Abstract: Skin cancer is one of the most prevalent cancers globally. Early and accurate diagnosis is critical for timely treatment and improved prognosis. This study presents a predictive modeling system for automated classification of skin lesions from dermoscopic images using deep neural networks and voting ensemble techniques. A customized 16-layer convolutional neural network architecture is developed for feature learning from lesion images. The concept of horizontal voting ensemble is implemented by …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 29–35 Read article
-
A Novel Analysis of Artificial Intelligence in Mechanical Engineering Application
Abstract: In this study, we have tried to explain the crucial role of Artificial Intelligence (AI) in the running of mechanical industry. The technology used these days in the machines is to aid the solution towards the real-world problems and complex situations. Many AI algorithms have been able to provide the solution to many engineering approaches. The importance of the artificial intelligence has automatized the mechanical engineering with smart machines and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 35–38 Read article
-
Effect of Different Configurations of Reinforcement and Post-Cure Temperature Detailed Survey
Abstract: Composites with natural fillers have applied many applications, such as interior housekeeping, building and so on but their findings are seldom examined in the mechanical, tribological and dynamic situation. The addition of fillers in GFRP composites enhances the mechanical, thermal and tribological properties due to filler occupied in voids in thermoset resin. There has also been a lot of work done in quantifying the consistency of the operating parameters through …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1738–1753 Read article
-
Multi-variable Analysis and Optimization of Electrical Discharge Machining Process Using a PCA-ANN Based Approach
Abstract: AbstractThe optimum selection of process parameters has played a crucial role in electrical discharge machining (EDM) for improving the material removal rate, reducing the tool wear rate and radial overcut. In this paper, optimum parameters while machining 202 stainless steel using copper electrode as a tool has been investigated. For optimization of process parameters along with multiple quality characteristics, principal component analysis coupled with artificial neural network method has been …
Published in Trends in Opto-electro & Optical Communication · Vol. 6, Issue 3, 2016 · pp. 39–45 Read article
-
Survey of Data Cleaning and Image Recognition using Neural Networks
Abstract: AbstractThis paper reviews the existing developments of data cl eaning and image recognition using neural networks At present most of the work in image recognition is done by using more than one method. Neural networks t ake the advantage a nd show good improvement in recognition of images In t his work, the authors hav e discusse d their advantages over traditional methods.Keywords: Data cleaning, image recognition, data transformation, artificial …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 1, 2014 · pp. 30–36 Read article
-
Human Skin Abnormality Detection with Process Similarity Criteria Fit Machine Learning Method
Abstract: This method presents a machine learning method that satisfies the defined conditions for healthy waterside beach activities. The boundary conditions of the normal and abnormal radiation spaces were formulated. The objectives of using a Regression Polynomial with Process Similarity Criteria Fit for skin temperature prediction are justified by the analysis of the existing analytical and machine learning approaches. An algorithm for skin temperature prediction using the theories of similarity criteria …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 17–24 Read article
-
Process Variable Optimization and Experimental Review of Aero-engine Blade using ECM
Abstract: AbstractProcess of blade in (EMC) can be effected by numerous factors, e.g., shape of blade, electrolytic liquid field and anodic dissolution, ECM parameters may result in affections on blade accuracy. Some aero-engine blade as research object, five main process parameters, voltage, machining gap, feed rate, temperature of working fluid and pressure variation of electrolyte inlet/outlet, are evaluated and optimized as per BP neural network Method. From 3125 possible operating parameter …
Published in Recent Trends in Sensor Research & Technology · Vol. 5, Issue 3, 2018 · pp. 27–32 Read article
-
To Study the VLF Signal for SeismoElectromagnetic Phenomena by Using Wavelet Analysis
Abstract: The research focuses on exploring the potential of Very Low Frequency (VLF) signals as indicators of seismic and geomagnetic activities, particularly in the context of earthquake prediction. It delves into the analysis of VLF data using wavelet-based methodologies and neural networks to detect anomalies preceding seismic events.Observations and analysis of VLF data revealed fluctuations and discrepancies, notably "silent days," occurring several days before seismic events. These irregularities studied through wavelet …
Published in Research & Reviews : Journal of Physics · Vol. 12, Issue 2, 2023 Read article
-
Review on Evaluation Techniques Such as DOE and ANN Used for Evaluate Heat Flow Parameters for Resistance Spot Welding
Abstract: Resistance spot welding is a widely used process of metal joining in industries. In resistance spot welding process, the time of welding is very little so, during welding process maintenance of high accuracy and precision is very difficult. Resistance spot welding has a wide application in automobile industry, household and domestic appliances manufacturing industry and fabrication industry like air craft manufacturing industry. For better output quality of product, save time …
Published in Trends in Mechanical Engineering & Technology · Vol. 5, Issue 3, 2015 · pp. 26–32 Read article
-
Network Traffic Analysis Using Machine Learning
Abstract: Network traffic analysis and prediction has applications in a variety of fields and has recently attracted a considerable number of studies. To find numerous issues with current computer network applications, various sorts of studies are carried out and reported. A proactive strategy to guarantee safe, dependable, and high-quality network communications is network traffic analysis and prediction. For network traffic analysis, several methods, including data mining and neural network-based methods, are …
Published in Current Trends in Signal Processing · Vol. 12, Issue 3, 2022 · pp. 17–23 Read article
-
Use of Intelligent Control Systems to Manage Traffic Effectively and Productively
Abstract: Intelligent control system is the advanced technology in which the collected data is provided to A.I. and with the help ofvarious methods like machine learning, neural networks, Bayesian probability, fuzzy logic the solution to a particularproblem is found.In a country’s growth the traffic management plays a great role as the maximum industries depends on the highways orroads and when it is well planned it can reduce the commute time and …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 22–27 Read article
-
Modeling of Sintering Process for the Preparation of Magnetic Abrasives by RSM and ANN Models
Abstract: In this study, a modeling has been done for the prediction of the sintering process, as sintering process is one of the best processes to prepare magnetic abrasives. The sintering process is modelled by using RSM and ANN techniques. The ANN model has been developed using a multilayer feed-forward neural network and trained with the help of an error backpropagation learning algorithm based on the generalized delta rule. The indication …
Published in Journal of Experimental & Applied Mechanics · Vol. 10, Issue 3, 2019 · pp. 5–12 Read article
-
FIR Filter Design using Artificial Neural Network
Abstract: In this paper design a low pass FIR filter by artificial neural network. For this kind of application, a different type of model is used in ANN. In this work, MLP Back propagation algorithm is used to train the Neural Network. MLP network is very effective method for filter designing process. We also compare the result of this method and the normal mathematical method. Keywords: Neural network, MLP back propagation, …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 3, Issue 3, 2013 · pp. 29–35 Read article
-
Object Recognition by Multi-Scale Color Local Binary Pattern
Abstract: This paper presents a multi-scale color local binary pattern based method for object recognition. Several advanced methods have been proposed for object recognition using deep neural networks. Although these methods offer high accuracy with many number of object classes, the high complexity of these methods requires large number of training examples and computational resources. This paper attempts to solve the object recognition problem for limited number of well known object …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 57s–61s Read article