Analysis of Quantum Computing Applications in Artificial Intelligence for Decision Support in Federal University, Birnin Kebbi, Kebbi State
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- NGN 5000
Background of the Study
Artificial Intelligence (AI) has revolutionized decision-making processes in various industries, including education. Universities, such as Federal University, Birnin Kebbi, face complex administrative, academic, and research-related decisions daily, which often require rapid and accurate data analysis. Traditional AI methods, including decision support systems (DSS), have been helpful, but they are often limited by computational power and the ability to process large datasets in real time. Quantum computing, with its ability to handle exponentially larger datasets and perform computations at unprecedented speeds, offers the potential to enhance AI algorithms used for decision support (Pistunovich et al., 2023).
Quantum computing’s unique ability to process multiple possibilities simultaneously makes it an ideal tool for improving decision-making in educational institutions. By integrating quantum computing into AI-based decision support systems, Federal University, Birnin Kebbi can develop more effective solutions for student performance prediction, resource allocation, and strategic planning. This study will explore the feasibility and impact of quantum computing in enhancing AI decision support models within the university setting.
Statement of the Problem
Despite the availability of traditional AI-based decision support systems, Federal University, Birnin Kebbi faces challenges in using these systems to process large volumes of data efficiently for decision-making. The speed and accuracy limitations of conventional systems hinder the university's ability to make timely and well-informed decisions. Given the potential of quantum computing to significantly enhance AI algorithms, it is essential to explore how quantum computing can improve the effectiveness of decision support systems in the university’s administrative and academic processes.
Objectives of the Study
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To analyze the potential applications of quantum computing in AI-based decision support systems for Federal University, Birnin Kebbi.
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To design a quantum-enhanced AI model for decision support in academic and administrative processes at the university.
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To assess the performance and feasibility of integrating quantum computing into existing AI-based decision support frameworks at the university.
Research Questions
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How can quantum computing be applied to enhance AI-based decision support systems at Federal University, Birnin Kebbi?
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What improvements in decision-making efficiency and accuracy can quantum computing bring to AI-based systems?
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What challenges may arise when integrating quantum computing into existing AI-based decision support systems?
Significance of the Study
This study will contribute to advancing decision support capabilities at Federal University, Birnin Kebbi, by incorporating quantum computing into AI models. The research will explore ways to improve the university’s ability to make better and faster decisions in various areas, including academic planning, resource allocation, and student performance monitoring. The findings will also offer valuable insights into the broader applications of quantum computing in educational decision-making.
Scope and Limitations of the Study
The study will focus on exploring the applications of quantum computing in AI-based decision support systems at Federal University, Birnin Kebbi, Kebbi State. The research will not delve into other potential applications of quantum computing outside of decision support systems and will be limited to the university's administrative and academic contexts.
Definitions of Terms
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Quantum Computing: A field of computing that leverages quantum mechanics principles to solve problems that are intractable for classical computers.
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Artificial Intelligence (AI): The simulation of human intelligence processes by machines, particularly in decision-making, learning, and problem-solving.
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Decision Support System (DSS): A computerized system used to support decision-making in organizations by analyzing large amounts of data and providing insights.
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