Ice in wind turbines may cause a tremendous reduction in energy conservation. As, ice over turbines are not considered to be a traditional weather prediction data, prediction towards power can leads to higher error. T...
Ice in wind turbines may cause a tremendous reduction in energy conservation. As, ice over turbines are not considered to be a traditional weather prediction data, prediction towards power can leads to higher error. This work anticipates a statistical approach dependent on Niave bayes regression to identify production loss has to be analyzed. It measures input of regional weather condition and various other conditions, and identify power production loss for 48 hours to enhance prediction of next generation energy loss. This can be trained with various prediction measurements and drastically enhances other conventional approaches for longer period. It may diminish absolute production error by ~100kW and it computes its skill with other models. Prediction of weather data is considered to be one of the effectual data for diverse statistical prediction and some calculations are not so absolute. This method can be computational less cost and may be trained again for next prediction.
作者：
N UmamaheswariR RenugadeviResearch Scholar
Department of Computer science Vels Institute of Science and Technology Advanced Studies (VISTAS) Chennai Assistant Professor
Department of Computer Science Vels Institute of Science and Technology Advanced Studies (VISTAS) Chennai
Cloud computing offers a technological revolution to the end-users need less infrastructure costs with virtualizes resources, and storage remains the insecure to delivers the scalability. The most common type of Distr...
Cloud computing offers a technological revolution to the end-users need less infrastructure costs with virtualizes resources, and storage remains the insecure to delivers the scalability. The most common type of Distributed Denial of Service DDoS attack, (denial of service), is a serious damage measure that affects virtual cloud users and Internet Service Providers (ISPs) are predominantly affects ongoing service attacks. I'm the recipient. These legacy of machine learning approach used to detect vulnerabilities to the attacker's leading network traffic intervention opening the door. By concentrating feature selection and classification approach with optimized neural network model to detect the DDoS type monitoring. This presents a deep neural network based DDoS detection system using Subset Feature Selection based Cascade Correlation Optimal Neural Network (SFS-C2ONN). The proposed approach is based on assumptions based on flow rate which is collected as dataset previously extracted from a model for network traffic. The test results shows that the sensitivity and specify based calcification approach which is suitable for the detection of neural network architecture and hyper parameters, and the optimizer DDoS attack. The results are obtained by calculating the accuracy of the attack detection.
This paper describes the process through which “Secured payment system using face recognition technique”- project has been made. It describes the main objective of the project which is to be able to develop a secure...
This paper describes the process through which “Secured payment system using face recognition technique”- project has been made. It describes the main objective of the project which is to be able to develop a secured and robust payment system using face recognition in python programming language with the help of OpenCV. It uses confidence value which can be described as the value generated by the system informing us about the accuracy of prediction. This project was made by combining various detection modules and pattern recognizer. In this project various existing methods are combined together to give us the result. Pin and one time password (OTP) are used for security measures to make safe and successful transaction. OTP will be sent to the registered phone number of the user.
At present, there is no solution whenever a live person or live animal was fallen from a building or from a high tower. To safeguard the live person, an IoT based adapter to be built whose purpose is to catch the obje...
At present, there is no solution whenever a live person or live animal was fallen from a building or from a high tower. To safeguard the live person, an IoT based adapter to be built whose purpose is to catch the object when a heavy movement is detected in the air. Any building from which a weighted object is dropped, that can be caught by netted sculpt that can get information from the proposed IoT based adapter fixed at someplace at the side view of the building. The components of this smart catcher are catcher device as IoT based adapter in which accurate position is predicted, netted wire with a built-in chip that takes location from the previous module, and catch the weighted object by the netted wire that can be directed by the built-in chip of it, and brings that object to the ground. Hence, the proposed methodology is the interconnection of networked devices that will communicate with each other in order to save the lives or any object that gets dropped from someplace of the high building. Its main advantage is eco-friendly nature and the latest technology adapted to figure out to catch the object that was falling from a remote high place. The sensors of the IoT-based adapter will scan and works to catch whenever the movement of the weighted object is detected. That sensed information to be sent to the chip of netted wire and netted wire will point to an accurate location to catch the object. The result is stored in a report that could be communicated to the nearest office.
Breast Cancer is the hazardous infection among young ladies and most significant reason for developing destruction rate. Physically anticipation of this affliction takes longer hours and structures are to be had in si...
Breast Cancer is the hazardous infection among young ladies and most significant reason for developing destruction rate. Physically anticipation of this affliction takes longer hours and structures are to be had in significantly less number, there's motivation to expand a mechanized forecast machine for early expectation and visualization of malignancy. The sort of considerate and threatening tumor are accomplished the use of type methodologies of device becoming acquainted with wherein the device is found from the past records and predicts the sorts of late sources of info. This paper is an overall report on the execution of models utilizing Logistic Regression, Support Vector Machine (SVM) and Gray wolf algorithm(GWO). The outcomes are assessed with the exactness, accuracy, affectability, explicitness and False Positive Rate boundaries for every calculation and are thought about. These procedures are coded in Java and executed in MATLAB, the Image handling Environment. Our investigations have demonstrated that Gray wolf is the best for prescient examination with an exactness of 92.7%.We surmise from our test results that SVM is the appropriate calculation for expectation and in general Gray wolf has performed well close to SVM.
Innovations in Machine Learning and Data Analytics can possibly affect numerous aspects of Environmental science (ES). Data Analytics refers to a collection of data resources indicated in terms of variety, velocity, v...
Innovations in Machine Learning and Data Analytics can possibly affect numerous aspects of Environmental science (ES). Data Analytics refers to a collection of data resources indicated in terms of variety, velocity, veracity and volume. Big data contributes to the ES arena in applications such as weather forecasting, energy sustainability and disaster management with the advent of techniques such as Remote Sensing, Information and Communication technologies. Though big data is used to accomplish data analysis and interpretation for ES, there are still requirements for efficient ways of data storage, processing and retrieval. Machine Learning and Deep Learning are the sub fields of artificial intelligence which deals with training the models to learn from data without being explicitly programmed. When Machine Learning and Deep Learning are combined together it is possible to unleash the supremacy of data analytics. These techniques show high prospective for process optimization, information-centric decision making and scientific discovery. Scientific developments like these will assist ES to make real time autonomous decisions by extracting useful insights from huge data. These advancements also aid in bridging the gap between the theoretical backgrounds on ES to practical implementation. The primary objective of this survey is to figure out the basic concepts of Machine Learning, Deep Learning, and Data Analytics and find the state-of-the-art applications in ES, and observe the impending benefits of information-centric investigation on ES.
We have obtained some results on oscillatory behavior of third order nonlinear neutral difference equations of the form where β and γ are odd integers with γ ≥ 1. Example is provided to illustrate the results.
We have obtained some results on oscillatory behavior of third order nonlinear neutral difference equations of the form where β and γ are odd integers with γ ≥ 1. Example is provided to illustrate the results.
作者：
S. Mahaboob BashaA. ArunT. D. SubhaV. BhuvaneswariD. KalaiSelviJ. Navin Sankar1Assistant Professor
Department of Electronics and Communication Engineering R.M.K. Engineering College R.S.M Nagar Kavaraipettai Tamil Nadu India 2Assistant Professor
Department of Computer Science and Engineering SRM Institute of Science and Technology SRM Nagar Kattankulathur Kanchipuram Chennai Tamil Nadu India 3Assistant Professor
Department of Electronics and Communication Engineering R.M.K. Engineering College R.S.M Nagar Kavaraipettai Tamil Nadu India 4Assistant Professor
Department of Electronics and Communication Engineering SRM Institute of Science and Technology City Campus Vadapalani Chennai Tamil Nadu India 5AP
Department of Electronics and Instrumentation Engineering R.M.D. Engineering College R.S.M Nagar Kavaraipettai Tamil Nadu India 6Application Engineer
Entuple Technologies Pvt Ltd Bangalore Karnataka India
The main aim of this work is to make the passengers to reach the station in the particular time. The microcontroller is used for prediction alert purpose. Nowadays frequently, during night time people are sleeping in ...
The main aim of this work is to make the passengers to reach the station in the particular time. The microcontroller is used for prediction alert purpose. Nowadays frequently, during night time people are sleeping in trains and miss their destination station are occurred. Hence, the valuable time is absent. Therefore, using AT89C52 microcontroller, RF controller and RF receiver module the project was designed to avoid such mistakes to alert the passengers and to wake up at the correct station by getting vibration automatically. The objective of this project is to use 89C52 microcontroller to alert the passengers about the station which he/she want to reach mechanically, using RF modules. In front of, 5Km ahead of the station may have transmitter tag to transmit the zone computing by RF signals. A receiver module placed in the seat to get the zone information, by fixing a watch which is to be used to alert the passenger with small vibration to awake.
Emotions play a vital role in human living and are correlated with every single word which is being spoken, without them life will be saturated and irrelevant. Understanding of the real apparent facial expressions mig...
Emotions play a vital role in human living and are correlated with every single word which is being spoken, without them life will be saturated and irrelevant. Understanding of the real apparent facial expressions might be difficult because part of the emotion might not be revealed outside by everyone. In the proposed method, the emotions of the human are analyzed in two different ways so that the real hidden emotion of the subject can be detected. Every human has unique brain waves, which gives better accuracy than other techniques. It ensures that the facial expression exhibited outside is real or not. The emotion analyzed will be useful in treating the person with high mental stress and also infinding the emotion of differently abled person who requires medical treatment.
Predictions of solar potential for these systems' production are important, whether they ensure sound activity or the perfect control of an energy discharge heading to the solar system. It is important to base the...
Predictions of solar potential for these systems' production are important, whether they ensure sound activity or the perfect control of an energy discharge heading to the solar system. It is important to base the prediction on solar irradiance before predicting solar systems performance. The measurement of solar radiation elements is a very significant criterion for applications of solar energy. Several globalized solar radiation prediction modes can be done in the two major categories: cloud imagery with physical models and machine learning techniques are correlated. In this paper, the methods used to predict solar radiation are explained with machine learning algorithms.
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