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人工智能与遗传算法组合运行下的独居青年情绪化卧室设计研究
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作者 李林子 王剑峰 +2 位作者 羊正形 崔臻 孟悦 《包装工程》 CAS 北大核心 2024年第S01期460-469,共10页
目的为缓解独居青年面临的巨大生活压力及其引发的情绪问题,提出一种能够有效改善其情绪状态的卧室设计方案。方法提出一种将人工智能DALL-E3与遗传算法(GA)相结合的空间优化方式对独居青年的卧室进行设计。在涉及多个设计参数的情况下... 目的为缓解独居青年面临的巨大生活压力及其引发的情绪问题,提出一种能够有效改善其情绪状态的卧室设计方案。方法提出一种将人工智能DALL-E3与遗传算法(GA)相结合的空间优化方式对独居青年的卧室进行设计。在涉及多个设计参数的情况下(如光线、颜色、材料等),遗传算法能够处理并优化这些参数,将优化后的参数导入人工智能DALL-E3中生成两种卧室场景方案。为提升用户对室内空间的满意度,采用层次分析法(AHP)与优劣解距离法(TOPSIS)相结合的方式对两种方案进行最优判定。结果通过将独居青年的卧室空间喜好调查结果带入遗传算法,生成符合用户情感标准的卧室空间方法。结论在国家对人工智能领域的利好政策支持下,基于遗传算法(GA)分析独居青年对空间设计的偏好,制定适合他们的卧室空间设计方案,并通过AHP-TOPSIS组合模型对设计方案的满意度进行验证。人工智能DALL-E3模型与遗传算法(GA)的结合在空间设计领域具有显著的指导作用和智能生成能力,为未来空间设计方向提供新的研究思路和方法。 展开更多
关键词 人工智能dall-e3 遗传算法 层次分析法 优劣解距离法 卧室空间设计
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Security Vulnerability Analyses of Large Language Models (LLMs) through Extension of the Common Vulnerability Scoring System (CVSS) Framework
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作者 Alicia Biju Vishnupriya Ramesh Vijay K. Madisetti 《Journal of Software Engineering and Applications》 2024年第5期340-358,共19页
Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, a... Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, and more. However, their widespread usage emphasizes the critical need to enhance their security posture to ensure the integrity and reliability of their outputs and minimize harmful effects. Prompt injections and training data poisoning attacks are two of the most prominent vulnerabilities in LLMs, which could potentially lead to unpredictable and undesirable behaviors, such as biased outputs, misinformation propagation, and even malicious content generation. The Common Vulnerability Scoring System (CVSS) framework provides a standardized approach to capturing the principal characteristics of vulnerabilities, facilitating a deeper understanding of their severity within the security and AI communities. By extending the current CVSS framework, we generate scores for these vulnerabilities such that organizations can prioritize mitigation efforts, allocate resources effectively, and implement targeted security measures to defend against potential risks. 展开更多
关键词 Common Vulnerability Scoring System (CVSS) Large Language Models (LLMs) dall-e Prompt Injections Training Data Poisoning CVSS Metrics
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