Context: Quantum software systems represent a new realm in software engineering, utilizing quantum bits (Qubits) and quantum gates (Qgates) to solve the complex problems more efficiently than classical counterparts . Agile software development approaches are considered to address many inherent challenges in quantum software development, but their effective integration remains unexplored Objective: This study investigates key causes of challenges that could hinders the adoption of traditional agile approaches in quantum software projects and develop an Agile Quantum Software Project Success Prediction Model (AQSSPM). Methodology: Firstly, w e identified 19 causes of challenging factors discussed in our previous study, which are potentially impacting agile quantum project success. Secondly, a survey was conducted to collect expert opinions on these causes and applied Genetic Algorithm (GA) with Na i ve Bayes Classifier (NBC) and Logistic Regression (LR) to develop the AQSSPM Results: Utilizing GA with NBC, project success probability improved from 53.17% to 99.68%, with cost reductions from 0.463% to 0.403%. Similarly, GA with LR increased success rates from 55.52% to 98.99%, and costs decreased from 0.496% to 0.409% after 100 iterati ons. Both methods result showed a strong positive correlation (rs=0.955) in causes ranking, with no significant difference between them (t=1.195, p=0.240>0.05). Conclusion: The AQSSPM highlights critical focus areas for efficiently and successfully implementing agile quantum projects considering the cost factor of a particular project

翻译：语境：量子软件系统代表了软件工程的新领域，它利用量子比特（Qubits）和量子门（Qgates）比经典系统更高效地解决复杂问题。敏捷软件开发方法被认为能应对量子软件开发中的诸多固有挑战，但两者的有效整合仍待探索。目的：本研究旨在探究阻碍传统敏捷方法在量子软件项目中应用的关键挑战成因，并开发敏捷量子软件项目成功预测模型（AQSSPM）。方法：首先，我们识别了先前研究中讨论的19项潜在影响敏捷量子项目成功的挑战因素成因；其次，通过问卷调查收集专家对这些成因的意见，并应用遗传算法（GA）结合朴素贝叶斯分类器（NBC）与逻辑回归（LR）来构建AQSSPM。结果：使用GA结合NBC时，项目成功概率从53.17%提升至99.68%，成本从0.463%降至0.403%；类似地，GA结合LR在100次迭代后成功率从55.52%升至98.99%，成本从0.496%降至0.409%。两种方法对成因排序显示出强正相关（rs=0.955），且无显著差异（t=1.195，p=0.240>0.05）。结论：AQSSPM突出了在考虑特定项目成本因素下，高效且成功实施敏捷量子项目的关键关注领域。