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BIKAS:Bio-Inspired Knowledge Acquisition and Simulacrum-A Knowledge Database to Support Multifunctional Design Concept Generation 认领 引用
1
作者 Pavan Tejaswi Velivela Yaoyao Fiona Zhao 《Data Intelligence》 EI 2024年第2期531-558,共28页
A detailed acquisition,analysis,and representation of biological systems exhibiting different functions is required to develop unique bio-inspired multifunctional conceptual designs and methods.This paper presents BIK... A detailed acquisition,analysis,and representation of biological systems exhibiting different functions is required to develop unique bio-inspired multifunctional conceptual designs and methods.This paper presents BIKAS:Bio-inspired Knowledge Acquisition and Simulacrum,a knowledge database of biological systems exhibiting various functionalities,developed based on case-based bio-inspired examples from literature.The knowledge database represents the biological features,their characteristics,and the function exhibited by the biological feature as a combination of its integrated structure and structural strategy.Furthermore,this knowledge database is utilized by the Expandable Domain Integrated Design(xDID)model that works on classifying,mapping,and representing biological features into their respective geometric designations called Domains.The combination of features from the Domains results in the generation of multifunctional conceptual designs.In addition,Meta-level design factors are proposed to aid designers in filtering the biological features and their respective functions having a similar structural strategy,thus aiding designers in rapidly selecting and emulating biological functions. 展开更多
关键词 Bio-inspired design(BID) Knowledge database Conceptual design Multifunctional bio-inspired design Agile innovation
Intelligent Information Management and Knowledge Discovery in Large Numeric and Scientific Databases 认领 引用 被引量：1
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作者 Patrick Perrin Frederick E. Petry & William Thomason 《Journal of Systems Engineering and Electronics》 1996年第2期73-86,共14页
The present article outlines progress made in designing an intelligent information system for automatic management and knowledge discovery in large numeric and scientific databases, with a validating application to th... The present article outlines progress made in designing an intelligent information system for automatic management and knowledge discovery in large numeric and scientific databases, with a validating application to the CAST-NEONS environmental databases used for ocean modeling and prediction. We describe a discovery-learning process (Automatic Data Analysis System) which combines the features of two machine learning techniques to generate sets of production rules that efficiently describe the observational raw data contained in the database. Data clustering allows the system to classify the raw data into meaningful conceptual clusters, which the system learns by induction to build decision trees, from which are automatically deduced the production rules. 展开更多
关键词 Knowledge discovery in databases Machine learning Decision tree inducers
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A New Approach for Knowledge Discovery in Distributed Databases Using Fragmented Data Storage Model 认领 引用
3
作者 Masoud Pesaran Behbahani Islam Choudhury Souheil Khaddaj 《Chinese Business Review》 2013年第12期834-845,共12页
Since the early 1990, significant progress in database technology has provided new platform for emerging new dimensions of data engineering. New models were introduced to utilize the data sets stored in the new genera... Since the early 1990, significant progress in database technology has provided new platform for emerging new dimensions of data engineering. New models were introduced to utilize the data sets stored in the new generations of databases. These models have a deep impact on evolving decision-support systems. But they suffer a variety of practical problems while accessing real-world data sources. Specifically a type of data storage model based on data distribution theory has been increasingly used in recent years by large-scale enterprises, while it is not compatible with existing decision-support models. This data storage model stores the data in different geographical sites where they are more regularly accessed. This leads to considerably less inter-site data transfer that can reduce data security issues in some circumstances and also significantly improve data manipulation transactions speed. The aim of this paper is to propose a new approach for supporting proactive decision-making that utilizes a workable data source management methodology. The new model can effectively organize and use complex data sources, even when they are distributed in different sites in a fragmented form. At the same time, the new model provides a very high level of intellectual management decision-support by intelligent use of the data collections through utilizing new smart methods in synthesizing useful knowledge. The results of an empirical study to evaluate the model are provided. 展开更多
关键词 data mining decision-support system distributed databases knowledge discovery in database （KDD）
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A Knowledge Based Approach to Integrated Battle Damage Assessment and Repair Analysis 认领 引用 被引量：1
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作者 Shi Quan Li Jianping Wang Runsheng 《International Journal of Plant Engineering and Management》 2000年第2期66-76,共11页
BDAR analysis is a kind of very complex analysis technology which can be used to determine the battle damage mode of equipment and relevant decision strategy. BDAR analysis is based on the information about FMEA/DMEA,... BDAR analysis is a kind of very complex analysis technology which can be used to determine the battle damage mode of equipment and relevant decision strategy. BDAR analysis is based on the information about FMEA/DMEA, MA(maintenance analysis), FTA(fault tree analysis) and vulnerability analysis. These information and analysis results are obtained on the basis of the domain expert's experience and knowledge. Upon the basis of the summary of BDARA methods, this paper provides applied knowledge database, puts forward BDARA's integrated thinking, implementing methods, and the key technology for IBDARA knowledge database's development. 展开更多
关键词 BDAR IBDARA knowledge database knowledge database approach.
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Human Body Information Database and Method of Application 认领 引用
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作者 ZHANG Li LI Yanmei 《International English Education Research》 2016年第7期112-114,共3页
This paper elaborate the emergence of human information database and the important role it plays in the various industries of economic development. It also interpret the primary human information database of current d... This paper elaborate the emergence of human information database and the important role it plays in the various industries of economic development. It also interpret the primary human information database of current domestic and abroad and analysis it＇s classification characteristic, Besides, this papers further explains how to make use of human information database and how to make the database to play its due value. In the end, the prospect of our country＇s body information database has been set forth, using relatively mature foreign database to improve Chinese body information database. 展开更多
关键词 database human body information data mining knowledge discovery in database
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A Neuro-genetic Based Short-term Forecasting Framework for Network Intrusion Prediction System 认领 引用 被引量：7
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作者 Siva S. Sivatha Sindhu S. Geetha +1 位作者 M. Marikannan A. Kannan 《International Journal of Automation and computing》 2009年第4期406-414,共9页
Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attac... Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by ＂authorized＂ users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system （IDS） is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference （KDD 2009） intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS （NGIDS） involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this work show that the system achieves improvement in terms of misclassification cost when compared with conventional IDS. The results of the experiments show that this system can be deployed based on a real network or database environment for effective prediction of both normal attacks and new attacks. 展开更多
关键词 Genetic algorithm intrusion detection system （IDS） neural networks weightage calculation knowledge discovery in databases （KDD） classification.
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Some Massively Parallel Algorithms from Nature 认领 引用
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作者 Li Yan Kang Li-shan +3 位作者 Chen Yu-ping Liu Pu Cao Hong-qing Pan Zheng-jun 《Wuhan University Journal of Natural Sciences》 EI CAS 2002年第1期37-46,共10页
We introduced the work on parallel problem solvers from physics and biology being developed by the research team at the State Key Laboratory of Software Engineering,Wuhan University.Results on parallel solvers include... We introduced the work on parallel problem solvers from physics and biology being developed by the research team at the State Key Laboratory of Software Engineering,Wuhan University.Results on parallel solvers include the following areas:Evolutionary algorithms based on imitating the evolution processes of nature for parallel problem solving,especially for parallel optimization and model-building;Asynchronous parallel algorithms based on domain decomposition which are inspired by physical analogies such as elastic relaxation process and annealing process,for scientific computations,especially for solving nonlinear mathematical physics problems.All these algorithms have the following common characteristics:inherent parallelism,self-adaptation and self-organization,because the basic ideas of these solvers are from imitating the natural evolutionary processes. 展开更多
关键词 evolutionary computation parallel algorithm imitating nature domain decomposition knowledge discovery in databases
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Form alizing Incomplete Knowledge in Incomplete Databases 认领 引用
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作者 沈一栋 《Journal of Computer Science & Technology》 SCIE EI 1992年第4期295-304,共10页
Up to now, no satisfactory theory has been established for formalizing incomplete knowledge in incomplete databases. In this paper, we clarify why existing closed world approaches, such as the CWA, the GCWA, the ECWA,... Up to now, no satisfactory theory has been established for formalizing incomplete knowledge in incomplete databases. In this paper, we clarify why existing closed world approaches, such as the CWA, the GCWA, the ECWA, circumscription, predicate completion and the PWA, fail to do so, and propose a new method. The method is an augmentation of both the ECWA and circumscrip- tion with the mechanism to discriminate implicitly expressed positive knowledge, negative knowledge and truly unknown knowledge. 展开更多
关键词 Form alizing Incomplete Knowledge in Incomplete Databases
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An Experimental Analysis of the Applications of Datamining Methods on Bigdata 认领 引用
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作者 CH.Naga Santhosh Kumar K.S.Reddy 《Journal of Autonomous Intelligence》 2019年第3期31-39,共9页
Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been br... Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been broadly utilized in the lifecycle of electronic items that range from the structure and generation stages to the administration organize.A far reaching examination of DM with Big Data and a survey of its application in the phases of its lifecycle won't just profit scientists to create solid research.As of late huge data have turned into a trendy expression,which constrained the analysts to extend the current data mining methods to adapt to the advanced idea of data and to grow new scientific procedures.In this paper,we build up an exact assessment technique dependent on the standard of Design of Experiment.We apply this technique to assess data mining instruments and AI calculations towards structure huge data examination for media transmission checking data.Two contextual investigations are directed to give bits of knowledge of relations between the necessities of data examination and the decision of an instrument or calculation with regards to data investigation work processes. 展开更多
关键词 Data Mining Big Data Knowledge Discovery Databases Decision Tree Cloud Data Mining K-Closest Neighbor Artificial Intelligence Cluster
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Framework and construction methodology of underground engineering domain knowledge large language model:UndergrGPT 认领 引用 被引量：4
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作者 Zhenhao Xu Zhaoyang Wang +2 位作者 Pengjie Ren Xiao Zhang Tianhao Li 《Smart Construction》 2024年第2期147-160,共14页
Large Language Models(LLMs)have achieved tremendous success in natural language processing tasks.However,in vertical domains such as underground engineering,the lack of large-scale structured corpora and the requireme... Large Language Models(LLMs)have achieved tremendous success in natural language processing tasks.However,in vertical domains such as underground engineering,the lack of large-scale structured corpora and the requirement for high-accuracy responses significantly increase the difficulty of constructing domain knowledge LLMs.Simultaneously,these challenges amplify the inherent flaws of models,such as machine hallucination and outdated content.To address the aforementioned challenges,firstly,we proposed a framework for constructing underground engineering domain knowledge LLMs,which includes human-machine collaborative knowledge extraction,parameter efficient fine-tuning,and retrieval-augmented generation.The framework aims to provide a universal construction paradigm for underground engineering domain knowledge LLMs.Secondly,within the proposed framework,we established an underground engineering domain knowledge database(UndergrData),introduced a domain knowledge extraction approach based on a few-shot prompt learning data augmentation strategy,resulting in the formation of the training dataset;we applied an underground engineering domain knowledge LLMs fine-tuning method under low-resource and constructed the first underground engineering domain knowledge LLM base(UndergrGPT);we adopted the approach of underground engineering domain knowledge retrieval-augmented generation,enabling high-quality response generation.Finally,compared with general LLMs,UndergrGPT effectively reduced hallucinations,demonstrating a significant advantage in response accuracy.It’s worth noting that the proposed framework can be extended to other vertical domains. 展开更多
关键词 domain knowledge large language model domain knowledge database construction framework knowledge extraction parameter efficient fine-tuning retrieval-augmented generation
An Overview of Data Mining and Knowledge Discovery 认领 引用 被引量：18
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作者 范建华 李德毅 《Journal of Computer Science & Technology》 SCIE EI 1998年第4期348-368,共21页
With massive amounts of data stored in databases, mining information and knowledge in databases has become an important issue in recent research. Researchers in many different fields have shown great interest in data ... With massive amounts of data stored in databases, mining information and knowledge in databases has become an important issue in recent research. Researchers in many different fields have shown great interest in data mining and knowledge discovery in databases. Several emerging applications in information providing services, such as data warehousing and on-line services over the Internet, also call for various data mining and knowledge discovery techniques to understand user behavior better, to improve the service provided, and to increase the business opportunities. In response to such a demand, this article is to provide a comprehensive survey on the data mining and knowledge discovery techniques developed recently, and introduce some real application systems as well. In conclusion, this article also lists some problems and challenges for further research. 展开更多
关键词 Knowledge discovery in databases data mining machine learning,association rule classification data clustering data generalization pattern searching
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Design and construction of knowledge ontology for thematic cartography domain 认领 引用 被引量：1
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作者 Tomas Penaz Radek Dostal +1 位作者 Isik Yilmaz Marian Marschalko 《Episodes》 SCIE 2014年第1期48-58,共11页
The paper deals with ontology modelling for the purpose of design and creating of knowledge ontology for thematic cartography.The prepared ontology represents a database of selected declarative cartographical knowledg... The paper deals with ontology modelling for the purpose of design and creating of knowledge ontology for thematic cartography.The prepared ontology represents a database of selected declarative cartographical knowledge subsequently employed in the intelligent system for interactive support of thematic map design.The knowledge system pilot project under development is intended for users without necessary cartographical knowledge to whom such system will enable interactive creation of a thematic map and will provide them with support to this aim.The paper brings up information on possibilities of a domain expert(cartographer)in the endeavour to seize domain knowledge of thematic cartography and to express them in a formalized way.OWL ontology concentrates,formalizes and organizes declarative knowledge of thematic cartography domain.The result is the database containing taxonomy of terms hierarchically arranged into categories as well as description of their mutual relations. 展开更多
关键词 knowledge system ontology modelling interactive creation thematic map database selected declarative cartographical knowledge knowledge ontology intelligent system design creating knowledge ontology thematic cartography
Knowledge Discovery and its Applications in Telecommunications Industry 认领 引用 被引量：2
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作者 WanYan SiYaqing 《The Journal of China Universities of Posts and Telecommunications》 1999年第1期46-51,共6页
It is important for telecom companies to make sense of the large number of data they have accumulated over the years. This paper reviews the concepts and the techniques of knowledge discovery in databases (KDD), and s... It is important for telecom companies to make sense of the large number of data they have accumulated over the years. This paper reviews the concepts and the techniques of knowledge discovery in databases (KDD), and surveys applications of this technology in the telecommunications sector all over the world. It also discusses some possible applications of this technology in China, and reports a preliminary result of the first attempt to apply KDD technique in telephone traffic volume prediction. It concludes that KDD is a promising technology that can help to enhance-the competitiveness of China's telecom companies in the face of looming competition in a liberated market. 展开更多
关键词 knowledge discovery in databases telecommunications data mining
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Rule Extraction from Trained Artificial Neural Network Based on Genetic Algorithm 认领 引用
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作者 WANGWen-jian ZHANGLi-xia 《Systems Science and Systems Engineering》 2002年第2期240-245,共6页
This paper discusses how to extract symbolic rules from trained artificial neural network (ANN) in domains involving classification using genetic algorithms (GA). Previous methods based on an exhaustive analysis of ne... This paper discusses how to extract symbolic rules from trained artificial neural network (ANN) in domains involving classification using genetic algorithms (GA). Previous methods based on an exhaustive analysis of network connections and output values have already been demonstrated to be intractable in that the scale-up factor increases with the number of nodes and connections in the network. Some experiments explaining effectiveness of the presented method are given as well. 展开更多
关键词 rule extraction neural network genetic algorithm knowledge discovery in database(KDD) data mining(DM)
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