本文關(guān)鍵詞：基于DFNN的智能配電異構(gòu)無(wú)線網(wǎng)絡(luò)準(zhǔn)入控制算法　出處：《現(xiàn)代電力》2014年06期 　論文類型：期刊論文

  更多相關(guān)文章： 智能配電網(wǎng) 異構(gòu)無(wú)線網(wǎng)絡(luò) 準(zhǔn)入控制 動(dòng)態(tài)模糊神經(jīng)網(wǎng)絡(luò) 阻塞率

【摘要】：為提高智能配電通信業(yè)務(wù)的服務(wù)質(zhì)量,根據(jù)智能配電網(wǎng)對(duì)通信技術(shù)的要求,提出一種基于動(dòng)態(tài)模糊神經(jīng)網(wǎng)絡(luò)(DFNN)的智能配電異構(gòu)無(wú)線網(wǎng)絡(luò)準(zhǔn)入控制算法。在智能配電網(wǎng)絡(luò)的異構(gòu)準(zhǔn)入控制模型中構(gòu)建神經(jīng)網(wǎng)絡(luò)系統(tǒng),以網(wǎng)絡(luò)的接入阻塞率差作為系統(tǒng)參數(shù)強(qiáng)化學(xué)習(xí)的目標(biāo),對(duì)網(wǎng)絡(luò)的負(fù)載均衡具有較好的動(dòng)態(tài)適應(yīng)性。神經(jīng)網(wǎng)絡(luò)系統(tǒng)在輸入層較多時(shí)容易產(chǎn)生太多規(guī)則而影響決策結(jié)果,而DFNN通過(guò)計(jì)算當(dāng)前系統(tǒng)規(guī)則的完備性,動(dòng)態(tài)添加規(guī)則,并通過(guò)計(jì)算所有規(guī)則的重要性,動(dòng)態(tài)刪除規(guī)則,使得系統(tǒng)的規(guī)則有效而不冗余。仿真結(jié)果表明,該方法較多接入選擇算法(MLB)明顯降低了網(wǎng)絡(luò)的接入阻塞率,相對(duì)于模糊神經(jīng)網(wǎng)絡(luò)算法(FNN)而言簡(jiǎn)化了系統(tǒng)結(jié)構(gòu),突出了規(guī)則的重要性,具有較低的接入阻塞率和更好的均衡效果。
[Abstract]:In order to improve the intelligent distribution communication quality of service, according to the requirements of intelligent distribution network communication technology, this paper proposed a dynamic fuzzy neural network (DFNN) based on the intelligent distribution of heterogeneous wireless network access control algorithm. In the heterogeneous access intelligent distribution network control based on neural network system model, the network access blocking rate is the difference the system parameters of reinforcement learning, has better dynamic adaptability to the network load balancing system based on neural network. The input layer is more easy to produce too many rules and the impact of the decision-making results, and through the calculation of the current DFNN completeness of system rules, add dynamic rules, and by calculating the importance of all the rules, dynamic delete rules, which makes the system the rules without redundancy. Simulation results show that the method of access selection algorithm (MLB) significantly reduces the network access blocking rate, phase The fuzzy neural network algorithm (FNN) simplifies the system structure, highlights the importance of the rules, has a lower access blocking rate and better balance effect.

【作者單位】： 新疆電力公司;華北電力大學(xué);
【分類號(hào)】：TM76;TN92
【正文快照】： 0引言在飛速發(fā)展的社會(huì)經(jīng)濟(jì)環(huán)境中,智能電網(wǎng)是未來(lái)提高電能質(zhì)量、加強(qiáng)企業(yè)服務(wù)水平等的重要工具[1-2]。作為智能配電網(wǎng)的重要組成部分,智能配電通信網(wǎng)是實(shí)現(xiàn)智能配電網(wǎng)的基礎(chǔ)[3]。其骨干網(wǎng)和部分接入網(wǎng)絡(luò)首選光纖通信網(wǎng)絡(luò),并輔以寬帶無(wú)線通信網(wǎng)絡(luò)方式[4-5]。但是在一些比較偏

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 陸一鳴;劉東;柳勁松;黃玉輝;凌萬(wàn)水;顧建煒;;智能配電網(wǎng)信息集成需求及模型分析[J];電力系統(tǒng)自動(dòng)化;2010年08期

2 黃盛;;智能配電網(wǎng)通信業(yè)務(wù)需求分析及技術(shù)方案[J];電力系統(tǒng)通信;2010年06期

3 陳樹勇;宋書芳;李蘭欣;沈杰;;智能電網(wǎng)技術(shù)綜述[J];電網(wǎng)技術(shù);2009年08期

4 林宇鋒;鐘金;吳復(fù)立;;智能電網(wǎng)技術(shù)體系探討[J];電網(wǎng)技術(shù);2009年12期

5 劉勝美;孟慶民;潘u&;糜正琨;;異構(gòu)無(wú)線網(wǎng)絡(luò)中基于SINR和層次分析法的SAW垂直切換算法研究[J];電子與信息學(xué)報(bào);2011年01期

6 石文孝;范紹帥;王g，

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