Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way ...Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way semi-concept lattices have three-way operators with weaker constraints,which can generate more concepts.In this article,the problem of rule acquisition for three-way semi-concept lattices is discussed in general.The authors construct the finer relation of three-way semi-concept lattices,and propose a method of rule acquisition for three-way semi-concept lattices.The authors also discuss the set of decision rules and the relationships of decision rules among object-induced three-way semi-concept lattices,object-induced three-way concept lattices,classical concept lattices and semi-concept lattices.Finally,examples are provided to illustrate the validity of our conclusions.展开更多
The characteristics of design process, design object and domain knowledge of complex product are analyzed. A kind of knowledge representation schema based on integrated generalized rule is stated. An AND-OR tree based...The characteristics of design process, design object and domain knowledge of complex product are analyzed. A kind of knowledge representation schema based on integrated generalized rule is stated. An AND-OR tree based model of concept for domain knowledge is set up. The strategy of multilevel domain knowledge acquisition based on the model is presented. The intelligent multilevel knowledge acquisition system (IMKAS) for product design is developed, and it is applied in the intelligent decision support system of concept design of complex product.展开更多
The acquisition of knowledge and the representation of that acquisition have always been viewed as the bottleneck in the construction of knowledge-based systems. The traditional methods of acquiring knowledge are base...The acquisition of knowledge and the representation of that acquisition have always been viewed as the bottleneck in the construction of knowledge-based systems. The traditional methods of acquiring knowledge are based on knowledge engineering and communication with field experts. However, these methods cannot produce systematic knowledge effectively, automatically construct knowledge-based systems, or benefit knowledge reasoning. It has been noted that, in specific professional fields, experts often use fixed patterns to describe their expertise in the scientific articles that they publish. Abstracts and conclusions, for example, are key components of the scientific article, containing abundant field knowledge. This paper suggests a method of acquiring production rules from the abstracts and conclusions of scientific articles in specific fields based on natural language comprehension. First, the causal statements in article abstracts and conclusions are extracted using existing techniques, such as text mining. Next, antecedence and consequence fragments are extracted using causal template matching algorithms. As the final step, part-of-speech-tagging production rules are automatically generated according to a syntax parsing tree from the speech pair sequence. Experiments show that this system not only improves the efficiency of knowledge acquisition but also simultaneously generates systematic knowledge and guarantees the accuracy of acquired knowledge.展开更多
Rough Set is a valid mathematical theory developed in recent years, which hasthe ability to deal with imprecise, uncertain, and vague information. This paper presents a newincremental rule acquisition algorithm based ...Rough Set is a valid mathematical theory developed in recent years, which hasthe ability to deal with imprecise, uncertain, and vague information. This paper presents a newincremental rule acquisition algorithm based on rough set theory. First, the relation of the newinstances with the original rule set is discussed. Then the change law of attribute reduction andvalue reduction are studied when a new instance is added. Follow, a new incremental learningalgorithm for decision tables is presented within the framework of rough set. Finally, the newalgorithm and the classical algorithm are analyzed and compared by theory and experiments.展开更多
随着复杂储层地震资料特征筛选的机器学习技术的进步,如何有效地对参与地震属性优选和储层反演的地震样本进行采集和分析,成为目前智能地震预测领域的一个研究热点。目前的方法多着重于模型分类算法的改进,在标签的制作和采集方面不仅...随着复杂储层地震资料特征筛选的机器学习技术的进步,如何有效地对参与地震属性优选和储层反演的地震样本进行采集和分析,成为目前智能地震预测领域的一个研究热点。目前的方法多着重于模型分类算法的改进,在标签的制作和采集方面不仅耗费大量时间进行人工标注,还存在标签不平衡情况下类内可靠性、类间平衡性不强等问题。为此,提出基于稀疏强特征提取的三维地震数据完备方法。首先,基于多数决原则的样本分割(Sample Segmentation Based on Majority Rule,SSMR)寻迹多尺度、多标签三维地震样本,进行采集、自动标注;然后,改进标签洗牌平衡方法(Improved Label Shuffling Balance Method,ILSB),通过“2+1”的样本增广平衡策略进行数据完备处理,改善样本采样不平衡性导致的模型训练偏向性;最后,利用基于最小L_(1)范数稀疏表示对奇异值分解结果进行强特征提取(Minimum L_(1)-norm Based Sparse Representation for Feature Extraction,L_(1)-SRFE)和可视化表示。实际资料应用表明,实钻井与验证井预测结果吻合度高,该方法具有较高的标签分类准确率。展开更多
基金Central University Basic Research Fund of China,Grant/Award Number:FWNX04Ningxia Natural Science Foundation,Grant/Award Number:2021AAC03203National Natural Science Foundation of China,Grant/Award Number:61662001。
文摘Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way semi-concept lattices have three-way operators with weaker constraints,which can generate more concepts.In this article,the problem of rule acquisition for three-way semi-concept lattices is discussed in general.The authors construct the finer relation of three-way semi-concept lattices,and propose a method of rule acquisition for three-way semi-concept lattices.The authors also discuss the set of decision rules and the relationships of decision rules among object-induced three-way semi-concept lattices,object-induced three-way concept lattices,classical concept lattices and semi-concept lattices.Finally,examples are provided to illustrate the validity of our conclusions.
文摘The characteristics of design process, design object and domain knowledge of complex product are analyzed. A kind of knowledge representation schema based on integrated generalized rule is stated. An AND-OR tree based model of concept for domain knowledge is set up. The strategy of multilevel domain knowledge acquisition based on the model is presented. The intelligent multilevel knowledge acquisition system (IMKAS) for product design is developed, and it is applied in the intelligent decision support system of concept design of complex product.
文摘The acquisition of knowledge and the representation of that acquisition have always been viewed as the bottleneck in the construction of knowledge-based systems. The traditional methods of acquiring knowledge are based on knowledge engineering and communication with field experts. However, these methods cannot produce systematic knowledge effectively, automatically construct knowledge-based systems, or benefit knowledge reasoning. It has been noted that, in specific professional fields, experts often use fixed patterns to describe their expertise in the scientific articles that they publish. Abstracts and conclusions, for example, are key components of the scientific article, containing abundant field knowledge. This paper suggests a method of acquiring production rules from the abstracts and conclusions of scientific articles in specific fields based on natural language comprehension. First, the causal statements in article abstracts and conclusions are extracted using existing techniques, such as text mining. Next, antecedence and consequence fragments are extracted using causal template matching algorithms. As the final step, part-of-speech-tagging production rules are automatically generated according to a syntax parsing tree from the speech pair sequence. Experiments show that this system not only improves the efficiency of knowledge acquisition but also simultaneously generates systematic knowledge and guarantees the accuracy of acquired knowledge.
基金This work is supported by National Science Foundation of China (No.60373111).
文摘Rough Set is a valid mathematical theory developed in recent years, which hasthe ability to deal with imprecise, uncertain, and vague information. This paper presents a newincremental rule acquisition algorithm based on rough set theory. First, the relation of the newinstances with the original rule set is discussed. Then the change law of attribute reduction andvalue reduction are studied when a new instance is added. Follow, a new incremental learningalgorithm for decision tables is presented within the framework of rough set. Finally, the newalgorithm and the classical algorithm are analyzed and compared by theory and experiments.
文摘随着复杂储层地震资料特征筛选的机器学习技术的进步,如何有效地对参与地震属性优选和储层反演的地震样本进行采集和分析,成为目前智能地震预测领域的一个研究热点。目前的方法多着重于模型分类算法的改进,在标签的制作和采集方面不仅耗费大量时间进行人工标注,还存在标签不平衡情况下类内可靠性、类间平衡性不强等问题。为此,提出基于稀疏强特征提取的三维地震数据完备方法。首先,基于多数决原则的样本分割(Sample Segmentation Based on Majority Rule,SSMR)寻迹多尺度、多标签三维地震样本,进行采集、自动标注;然后,改进标签洗牌平衡方法(Improved Label Shuffling Balance Method,ILSB),通过“2+1”的样本增广平衡策略进行数据完备处理,改善样本采样不平衡性导致的模型训练偏向性;最后,利用基于最小L_(1)范数稀疏表示对奇异值分解结果进行强特征提取(Minimum L_(1)-norm Based Sparse Representation for Feature Extraction,L_(1)-SRFE)和可视化表示。实际资料应用表明,实钻井与验证井预测结果吻合度高,该方法具有较高的标签分类准确率。
