本文選題：泛在網(wǎng) + 模糊推理�。� 參考：《南京理工大學(xué)》2014年碩士論文

【摘要】：當(dāng)前,國(guó)內(nèi)外的許多城市都在推進(jìn)“泛在城市”、“智慧城市”研究與建設(shè),希望以此為契機(jī)帶動(dòng)整個(gè)信息產(chǎn)業(yè),乃至促進(jìn)經(jīng)濟(jì)和社會(huì)的發(fā)展。泛在網(wǎng)中,最為核心的問(wèn)題是如何確保異構(gòu)終端間進(jìn)行可信的通信。只有讓異構(gòu)終端實(shí)現(xiàn)了可信交互,才能實(shí)現(xiàn)多種異構(gòu)終端間的通信,才能真正實(shí)現(xiàn)“泛在”。 現(xiàn)在的大部分信任模型中,推薦服務(wù)僅提供了一種單一的信任值作為推薦。但是由推薦者提供的這種單一信任值代表了它對(duì)未知實(shí)體的主觀觀點(diǎn),不能很好的反映出在某種特定環(huán)境下的信任等級(jí)。為解決這個(gè)問(wèn)題,本文提出了一種有效的基于可信度的間接信任計(jì)算方法。該間接信任計(jì)算方法不僅能計(jì)算出每個(gè)誠(chéng)實(shí)推薦的可信度,還可以對(duì)不誠(chéng)實(shí)的推薦進(jìn)行過(guò)濾。 其次,本文提出了一種基于信譽(yù)和模糊理論的綜合信任模型CFMBRF,該模型采用“基于可信度的間接信任計(jì)算方法”作為間接推薦的方法,并在信譽(yù)模型的基礎(chǔ)上,引入模糊推理子系統(tǒng),使其能處理“交互重要性”、“不確定區(qū)域的決策”和“交互結(jié)果的設(shè)定”等主觀概念,可以人性化的執(zhí)行不確定性的決策。 最后進(jìn)行了大量的仿真實(shí)驗(yàn)。一方面,對(duì)“基于可信度的間接信任計(jì)算方法”的有效性進(jìn)行驗(yàn)證,結(jié)果證明該間接信任計(jì)算方法不僅能夠過(guò)濾不誠(chéng)實(shí)的推薦,還能計(jì)算出每個(gè)誠(chéng)實(shí)推薦的可信度。另一方面,對(duì)沒(méi)有使用任何模糊子系統(tǒng)的網(wǎng)絡(luò)和使用了模糊子系統(tǒng)的網(wǎng)絡(luò)進(jìn)行模擬和對(duì)比分析,并測(cè)試了CFMBRF模型的系統(tǒng)開(kāi)銷(xiāo)和穩(wěn)定性。實(shí)驗(yàn)結(jié)果表明使用了模糊子系統(tǒng)之后,終端間交互的正確性大幅提高,信譽(yù)向量的查詢(xún)次數(shù)明顯減少,證明了CFMBRF模型的有效性。
[Abstract]:At present, many cities at home and abroad are promoting the research and construction of "ubiquitous cities" and "wise cities", hoping to take this opportunity to drive the whole information industry and even promote the development of economy and society. In ubiquitous networks, the core problem is how to ensure credible communication between heterogeneous terminals. Only when the heterogeneous terminal realizes the trusted interaction, can the communication between the heterogeneous terminals be realized, and the "ubiquitous" can be realized. In most trust models today, recommendation services provide only a single trust value as a recommendation. However, the single trust value provided by the referees represents its subjective view of the unknown entity, and does not reflect the trust level in a certain environment. In order to solve this problem, this paper proposes an effective indirect trust calculation method based on credibility. The indirect trust calculation method can not only calculate the credibility of each honest recommendation, but also filter dishonest recommendation. Secondly, a comprehensive trust model based on reputation and fuzzy theory is proposed in this paper. The model adopts "indirect trust calculation method based on credibility" as the indirect recommendation method, and based on the credibility model. The fuzzy inference subsystem is introduced to deal with the subjective concepts such as "interaction importance", "decision of uncertain region" and "setting of interactive result", which can humanize the execution of uncertain decision. Finally, a large number of simulation experiments are carried out. On the one hand, the validity of "indirect trust computing method based on credibility" is verified. The results show that the indirect trust calculation method can not only filter dishonest recommendations, but also calculate the credibility of each honest recommendation. On the other hand, the network without any fuzzy subsystem and the network with fuzzy subsystem are simulated and compared, and the system overhead and stability of CFMBRF model are tested. The experimental results show that the correctness of the interaction between terminals is greatly improved and the query times of the reputation vector are obviously reduced after the fuzzy subsystem is used, which proves the validity of the CFMBRF model.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TP393.08

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本文編號(hào)：1981990