Výsledky vyhledávání - "Selvakanmani, S."

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Liver Infection Prediction Analysis using Machine Learning to Evaluate Analytical Performance in Neural Networks by Optimization Techniques

Autor: Deivendran, P., Selvakanmani, S., Jegadeesan, S., Kumar, V. Vinoth

Liver infection is a common disease, which poses a great threat to human health, but there is still able to identify an optimal technique that can be used on large-level screening. This paper deals with ML algorithms using different data sets and pre

Externí odkaz: http://arxiv.org/abs/2305.07670

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Optimizing E-waste management: Deep learning classifiers for effective planning

Autor: Selvakanmani, S., Rajeswari, P., Krishna, B.V., Manikandan, J.

Publikováno v: In Journal of Cleaner Production 1 March 2024 443

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Deep learning approach to solve image retrieval issues associated with IOT sensors

Autor: Selvakanmani, S., B, Ashreetha, Devi, G. Naga Rama, Misra, Shubhrojit, R, Jayavadivel, Perli, Suresh Babu

Publikováno v: In Measurement: Sensors December 2022 24

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Strategic Improved K-Means Clustering in Mining Blood Donor Data Analysis and IoT-based Allocation.

Autor: Tiwari, Vibha, Gowthami, Chopparapu, R., Bhavani, Kayalvizhi, S., Selvakanmani, S., Edara, Deepak Chowdary

Publikováno v: Journal of Intelligent Systems & Internet of Things; 2024, Vol. 13 Issue 1, p122-134, 13p

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A Review of routing protocols for mobile cognitive radio ad hoc networks

Autor: Selvakanmani, S., Sumathi, M.

Ad hoc network is a collection of wireless mobile nodes that dynamically form a temporary network without the use of any existing network infrastructure or centralized administration. A cognitive radio is a radio that can change its transmitter param

Externí odkaz: http://arxiv.org/abs/1207.5734

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Nature-Inspired Optimisation-Based Regression Based Regression to Study the Scope of Professional Growth in Small and Medium Enterprises

Autor: Pattnaik, Manjula, Sunil Kumar, M., Selvakanmani, S., Kudale, Kaniphnath Malhari, M., Kumarasamy, Girimurugan, B.

Publikováno v: International Journal of Intelligent Systems and Applications in Engineering; Vol. 11 No. 4s (2023); 100-108

Manufacturing firms are currently during the Fourth Industrial Revolution, which is in the process of progressing, and as a result, they are facing new issues related to technology, organizational structure, and management. It is anticipated that con

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=issn21476799::c43465923fb43b036b05a0b8e9394bd1
https://www.ijisae.org/index.php/IJISAE/article/view/2576

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