Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16759
Title: A Method Leveraging AI to Forecast Employee Performance During Work Hours and Propose Appropriate Salary Adjustments
Authors: Sharma, Kuldeep
Sukheswala, Jenish
Yadav, Brijendra Singh
Londhe, Gaurav Vishnu
Singh, Rohit
Pallathadka, Harikumar
Keywords: Ai Forecasting
Ai-Driven Compensation Modeling
Employee Performance Prediction
Performance Optimization
Salary Adjustment Recommendation
Work Hour Analysis
Workplace Productivity Enhancement
Issue Date: 2024
Publisher: Proceedings - 3rd International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2024
Institute of Electrical and Electronics Engineers Inc.
Abstract: This paper presents a new approach exercising artificial intelligence(AI) to prognosticate hand performance dynamics throughout work hours, easing informed opinions regarding payment adaptations. using advanced AI algorithms, the proposed system integrates colorful factors similar to literal performance data, real-time criteria, and contextual variables to induce accurate performance vaticinations. By assaying patterns and trends in hand geste and productivity, the model offers precious perceptivity into implicit oscillations in performance situations during the course of the workday. also, grounded on these vaticinations, the system suggests applicable payment adaptations acclimatized to individual performance circles, thereby optimizing compensation structures for enhanced hand provocation and organizational productivity. Through empirical confirmation and case studies, the efficacity and trustability of the proposed system are demonstrated, pressing its eventuality to revise performance operation practices and foster a further indifferent and satisfying work terrain. © 2024 IEEE.
URI: https://doi.org/10.1109/ACCAI61061.2024.10601739
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16759
ISBN: 9798350389432
Appears in Collections:Conference Papers

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