Titlebook: Artificial Intelligence and Evolutionary Computations in Engineering Systems; Subhransu Sekhar Dash,C. Lakshmi,Bijaya Ketan Pani Conferenc

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Comparative Analysis and Performance of DSTATCOM Device Using PI and Second-Order Sliding Mode Contevices used in the distribution network. In distribution systems, it is around 75% problems which are caused due to especially harmonics. Harmonics exists due to nonlinear devices used in distribution system. These harmonics are compensated by a distribution static compensator (DSTATCOM). By using t

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Stock Market Prediction Using Long Short-Term Memory,s not the case every time due to the ever wavering nature of the markets. To minimize the risk of loss due to drastically changing market, people have come up with many predictive models to simulate the future of stock markets. This paper presents a model that can predict the stock market. The use o

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gangrene

Automatic Generation Control Using Novel PD Plus FOPI Controller Tuned by Salp Swarm Algorithm,y (i) an abrupt load deviation of magnitude 0.01 per unit in control area 1 and (ii) abrupt load deviation of magnitude 0.06 per unit in control area 1. The later investigation also reveals that projected controller is robust as it can successfully manage the frequency abnormalities without further

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,A Detailed Analysis of Intruders’ Activities in the Network Through the Real-Time Virtual Honeynet ll give insight to the readers and security practitioners to understand the strategies followed by the attackers as well as the way of designing different traps to secretly follow the attackers in the road toward foolproof safeguarding mechanisms.

convulsion

Optimization of Big Data Using Rough Set Theory and Data Mining for Textile Applications,this research paper addresses this issue in depth. We propose a new algorithm scalable rough priority prediction model (SrPPM) to predict fabric width of single jersey finished cotton?knitted fabric with real-time textile big dataset over?Hadoop MapReduce framework. Our results show that our propose

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灰心喪氣

An Effective Approach for Plant Monitoring, Classification and Prediction Using IoT and Machine Lea moisture content falls below a certain threshold. The second part aims to analyse the Blynk collected data to classify the plant based on its conditions, i.e. healthy or unhealthy. Finally, we compare the performance results of support vector machine, random forest and logistic regression for class

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Intelligent Wireless Sensor Networks for Precision Agriculture,hich helps in predicting the growth of the plant. By knowing the growth rate of the plant, a farmer can tweak this rate with the amount of water he pours and a prediction is provided for the growth of the plant. This way there is no excess amount of water used on the plant which may harm the plant.

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