2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)最新文献_第7页

Classification of SSVEP Signals using Neural Networks for BCI Applications 基于脑机接口应用的SSVEP信号分类

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862368

Rebba Prashanth Kumar, Sangineni Siri Vandana, Dushetti Tejaswi, K. Charan, Ravichander Janapati, Usha Desai

引用次数: 3

Full-Bridge DC-DC Converter and Boost DC-DC Converter with Resonant Circuit For Plug-in Hybrid Electric Vehicles 插电式混合动力汽车全桥DC-DC变换器和带谐振电路的升压DC-DC变换器

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862426

Lalmalsawmi, P. Biswas

引用次数: 2

Review of Gaussian Mixture Model-Based Probabilistic Load Flow Calculations 基于高斯混合模型的概率潮流计算综述

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862332

B. Prusty, Kishore Bingi, Neeraj Gupta

引用次数: 0

Combined ALFC-AVR Control of Diverse Energy Source Based Interconnected Power System using Cascade Controller 基于级联控制器的多能量互联电力系统ALFC-AVR联合控制

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862433

Biswanath Dekaraja, L. Saikia, Satish Kumar Ramoji

{"title":"Combined ALFC-AVR Control of Diverse Energy Source Based Interconnected Power System using Cascade Controller","authors":"Biswanath Dekaraja, L. Saikia, Satish Kumar Ramoji","doi":"10.1109/ICICCSP53532.2022.9862433","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862433","url":null,"abstract":"This article presents a novel fractional-order (FO) cascade controller named FO tilt-derivative with filter cascaded to FO proportional-derivative with filter (CFOTDN-FOPDN) controller for unified automatic load frequency control study considering automatic voltage regulator loop. The considered system includes hydro and dish-Stirling solar thermal system in area-1 and area-2 consists of thermal and solar thermal power plant. Pertinent physical constraints are provided to the thermal and hydro units. The communication time delay (CTD) among load dispatch center and location of the power generation unit is considered. The optimization method named artificial flora algorithm is utilized to accomplish superlative solution. Investigations reveal that the proposed controller outperforms the PIDN and TIDN controllers. Analysis reflects that the higher value of CTD degrades the system performance. Moreover, the system performance improves with the higher value of the solar insolation. Lastly, the sensitivity analysis divulges the AFA optimized controller parameters are more robust against wide variations of system loading.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127700764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coordinated Control of EV Charging stations for Grid Frequency Support 电网频率支持下电动汽车充电站的协调控制

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862331

S. Anbuselvi, R. Devi, R. Brinda

引用次数: 0

Development and Testing of V-8 Electromagnetic Engine V-8电磁发动机的研制与试验

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862456

Vraj Patel, Jayant Vagajiyani, Rushikesh Nayi, Dhaval Sagar, Jay Rakholiya, Sathish Dharmalingam

{"title":"Development and Testing of V-8 Electromagnetic Engine","authors":"Vraj Patel, Jayant Vagajiyani, Rushikesh Nayi, Dhaval Sagar, Jay Rakholiya, Sathish Dharmalingam","doi":"10.1109/ICICCSP53532.2022.9862456","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862456","url":null,"abstract":"The electromagnetic engine is similar to the conventional internal combustion engines that are commonly utilized to meet daily demands. With the growing population, there are many chances that non-renewable resources may be depleted in the near future. As a result, those resources have been depleted, and pollution has increased. As a result, it's critical to create an engine that can function with a different alternative or source. Internal combustion engines use fossil fuels, which are inefficient since they emit a lot of pollution and are nonrenewable energy sources. The construction of an electromagnetic engine can address all of these concerns. The magnetic qualities of repulsion and attraction are used to operate the electromagnetic engine. The connecting rod, piston, crankshaft, and other components of a classic internal combustion engine are included in this system. This project's purpose is to develop and build an electromagnetic engine that can power an unmanned aerial vehicle's propeller. The engine has been tested for voltage ranges from 12 V to 24 V. Force, torque, and efficiency have been calculated. Airspeed behind the propeller and RPM have been measured using a pitot-static probe and a tachometer, respectively.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121522430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of Indian government stakeholder oil stock prices using hyper parameterized LSTM models 利用超参数化LSTM模型预测印度政府利益相关者石油价格

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862425

A. K. Singh, Joyjit Patra, Monalisa Chakraborty, Subir Gupta

{"title":"Prediction of Indian government stakeholder oil stock prices using hyper parameterized LSTM models","authors":"A. K. Singh, Joyjit Patra, Monalisa Chakraborty, Subir Gupta","doi":"10.1109/ICICCSP53532.2022.9862425","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862425","url":null,"abstract":"An investment is capturing money to profit from it. Investing has become a buzzword among middle-class households. People can invest their money in a variety of ways. Land, gold, jewels, cash, mutual funds, and the stock market may all make investments. We all know how volatile the stock market is. But why is it beneficial to middle-class families? For example, a man from a middle-class family may want to buy land, but it may be too expensive. However, it is possible to obtain a share for a pittance. The disparity between investment and result is apparent here. Forecasting is challenging due to the volatility and non-linearity of financial stock markets. Artificial intelligence and increased computing power have enhanced accuracy in stock price prediction programs. In this paper, we consider Bharat Petroleum Corporation Limited (BPCL), Hindustan Petroleum Corporation Limited (HPCL), and Indian Oil Corporation (I.O.C.) to be the government oil corporations with the most significant stake in the Indian petroleum industry. This paper enhances the prediction of effect by combining a hybridized model of Machine Learning with a Data Science model. Machine Learning-based Hyper Parameter Tuning of Neural Network LSTM has been used to estimate the following day closing price for three equity from Indian government oil industries. The open and close stock prices are considered when creating new model input variables. This project's accuracy is around 99 percent.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132601089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Modeling and Performance Analysis of a Closed Loop PEMFC in Small Scale Stand Alone DC System 小型独立直流系统中闭环PEMFC的建模与性能分析

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862402

Snehashis Ghoshal, Sumit Banerjee, Sweta, Rakesh Maji, Nehal Akhter, C. K. Chanda

引用次数: 0

Deep Neural Network-based Single Object Tracking 基于深度神经网络的单目标跟踪

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862438

Shiv Kumar, Sandeep Kumar Singh

引用次数: 0

Underwater Fish Detection and Classification using Deep Learning 基于深度学习的水下鱼类检测与分类

2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) Pub Date : 2022-07-21 DOI: 10.1109/ICICCSP53532.2022.9862410

Vrushali Pagire, A. Phadke

{"title":"Underwater Fish Detection and Classification using Deep Learning","authors":"Vrushali Pagire, A. Phadke","doi":"10.1109/ICICCSP53532.2022.9862410","DOIUrl":"https://doi.org/10.1109/ICICCSP53532.2022.9862410","url":null,"abstract":"The researchers face a difficult problem in detecting and identifying underwater fish species. Marine researchers and ecologists must evaluate the comparative profusion of fish species in their environments on a regular basis and track population trends. Researchers have presented a number of underwater computer vision, machine learning-based automatic systems for fish detection and classification. However, due of the changing undersea environment, it is extremely challenging to find the ideal system for detecting and classifying fish. Because light has such a strong influence in the aqueous medium, conducting research in this environment is difficult. The MobileNet model is utilised to detect and recognise the fish breed in the proposed work. The dataset is preprocessed before the model is implemented in order to obtain appropriate performance metrics. The work is based on the Kaggle dataset, which has nine different fish breeds in total. With a 99.74 percent accuracy, the model can detect and recognise nine different breeds. In comparison to other state of art methods, the model exhibits promising results.","PeriodicalId":326163,"journal":{"name":"2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128321016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1