本文選題：認(rèn)知智能 + 不確定信息��； 參考：《合肥工業(yè)大學(xué)》2017年博士論文

【摘要】：模擬人的意識(shí)、思維過(guò)程是一門極富挑戰(zhàn)性的科學(xué)。本文針對(duì)傳統(tǒng)認(rèn)知系統(tǒng)單向開(kāi)環(huán)方式與人類認(rèn)知事物反復(fù)推敲比對(duì)的信息交互過(guò)程存在顯著差異問(wèn)題,面對(duì)認(rèn)知系統(tǒng)中可識(shí)別率與正確率不可在線實(shí)時(shí)測(cè)評(píng)的工程難題,探討了不確定信息認(rèn)知對(duì)象建模、廣義認(rèn)知誤差度量和仿反饋調(diào)節(jié)機(jī)制三位一體的仿人認(rèn)知智能新研究方法�；诖植诩碚�,探索建立不確定信息認(rèn)知對(duì)象的模式化結(jié)構(gòu)模型和運(yùn)行機(jī)制�；趶V義誤差理論與熵理論,探索建立廣義認(rèn)知誤差的多層次變粒度熵函數(shù)形式測(cè)度指標(biāo)評(píng)價(jià)體系�；诜答伩刂扑枷牒驼J(rèn)知知識(shí)粒度計(jì)算工具,探索建立具有仿反饋模式的認(rèn)知智能運(yùn)行機(jī)制。力圖對(duì)一類不確定信息認(rèn)知對(duì)象和不確定認(rèn)知過(guò)程效果與認(rèn)知結(jié)果的認(rèn)知智能系統(tǒng)建立仿人反復(fù)推敲比對(duì)思維信息交互模式的認(rèn)知智能機(jī)制與計(jì)算模型,這對(duì)于人工智能學(xué)科的發(fā)展具有拓展意義。本文取得的主要研究成果如下:(1)不確定信息認(rèn)知對(duì)象仿反饋認(rèn)知智能系統(tǒng)的結(jié)構(gòu)與運(yùn)行機(jī)制研究。構(gòu)建一種仿人認(rèn)知事物粗推敲細(xì)比對(duì)反復(fù)交互模式的三層三段互耦合仿反饋認(rèn)知智能系統(tǒng)的結(jié)構(gòu)模式與運(yùn)行機(jī)制,給出了仿反饋認(rèn)知智能系統(tǒng)的構(gòu)建目標(biāo),規(guī)范了功能要求和運(yùn)行機(jī)制,為建立不確定信息認(rèn)知對(duì)象的仿反饋認(rèn)知智能系統(tǒng)提供了模式化結(jié)構(gòu)的構(gòu)建方法。(2)不確定信息認(rèn)知對(duì)象的認(rèn)知智能決策信息系統(tǒng)模型研究。針對(duì)目前學(xué)術(shù)界普遍認(rèn)為不存在能夠適應(yīng)于各種數(shù)據(jù)的通用知識(shí)獲取方法問(wèn)題,構(gòu)建了基于粗糙集的不確定信息認(rèn)知對(duì)象的多信息融合有監(jiān)督學(xué)習(xí)認(rèn)知智能決策信息系統(tǒng),給出了基于特征簡(jiǎn)約的認(rèn)知知識(shí)融合充分性和可分類性熵函數(shù)形式測(cè)度指標(biāo),在有限論域的不確定信息條件下,為不確定信息認(rèn)知對(duì)象的認(rèn)知知識(shí)優(yōu)化表征提供了普適性的認(rèn)知智能決策信息系統(tǒng)模型。(3)不確定認(rèn)知過(guò)程效果與認(rèn)知結(jié)果的廣義認(rèn)知誤差評(píng)價(jià)體系研究。針對(duì)目前學(xué)術(shù)界普遍采用后驗(yàn)評(píng)價(jià)認(rèn)知結(jié)果可信度方法不能滿足認(rèn)知系統(tǒng)中可識(shí)別率與正確率的在線實(shí)時(shí)測(cè)評(píng)問(wèn)題,構(gòu)建了不確定信息認(rèn)知對(duì)象和不確定認(rèn)知過(guò)程效果與認(rèn)知結(jié)果的認(rèn)知誤差信息系統(tǒng),定義了基于熵函數(shù)形式測(cè)度指標(biāo)的不確定認(rèn)知過(guò)程效果與認(rèn)知結(jié)果誤差熵、不確定認(rèn)知過(guò)程效果與認(rèn)知結(jié)果誤差熵序列相似度和認(rèn)知知識(shí)粒度誤差三種廣義認(rèn)知誤差,建立了不確定認(rèn)知過(guò)程效果與認(rèn)知結(jié)果可信度在線實(shí)時(shí)測(cè)評(píng)體系,為仿反饋認(rèn)知智能調(diào)節(jié)機(jī)制提供了量化標(biāo)準(zhǔn)。(4)不確定信息認(rèn)知對(duì)象的仿反饋認(rèn)知智能機(jī)制研究。針對(duì)傳統(tǒng)認(rèn)知系統(tǒng)單向開(kāi)環(huán)方式與人類認(rèn)知事物反復(fù)推敲比對(duì)的信息交互過(guò)程存在顯著差異問(wèn)題,構(gòu)建了基于廣義認(rèn)知誤差在線實(shí)時(shí)度量的仿反饋認(rèn)知智能調(diào)節(jié)機(jī)制,定義了仿反饋認(rèn)知知識(shí)粒度調(diào)節(jié)規(guī)則與計(jì)算方法,建立了多層次變知識(shí)粒度的層間調(diào)節(jié)與層內(nèi)尋優(yōu)模式,實(shí)現(xiàn)對(duì)不確定信息認(rèn)知對(duì)象的變知識(shí)粒度的仿反饋認(rèn)知智能調(diào)節(jié)機(jī)制,為模仿人類認(rèn)知事物反復(fù)推敲比對(duì)的信息交互過(guò)程提供了一種智能認(rèn)知機(jī)制。(5)單目標(biāo)完全狀態(tài)的脫機(jī)手寫(xiě)體漢字圖像的機(jī)器認(rèn)知應(yīng)用驗(yàn)證研究。針對(duì)手寫(xiě)體漢字?jǐn)?shù)量大,字體字型繁多,相似字多,書(shū)寫(xiě)風(fēng)格各異等識(shí)別難題,基于本文提出的仿反饋認(rèn)知智能方法,研究了具有認(rèn)知知識(shí)粒度智能調(diào)節(jié)機(jī)制的脫機(jī)手寫(xiě)體漢字圖像仿反饋認(rèn)知智能系統(tǒng)。選用SCUT-IRAC HCCLIB手寫(xiě)體漢字圖像樣本庫(kù)的多類漢字樣本圖像作為認(rèn)知對(duì)象,進(jìn)行了仿真實(shí)驗(yàn)以驗(yàn)證本方法的可行性與有效性。實(shí)驗(yàn)結(jié)果表明,本文方法較傳統(tǒng)單向開(kāi)環(huán)方法具有明顯優(yōu)勢(shì),為實(shí)現(xiàn)對(duì)脫機(jī)手寫(xiě)體漢字圖像的“機(jī)器識(shí)字”代替“人工識(shí)字”探索了一種實(shí)踐應(yīng)用新方法。(6)多目標(biāo)較完全狀態(tài)的工業(yè)回轉(zhuǎn)窯燒成狀態(tài)的機(jī)器認(rèn)知應(yīng)用驗(yàn)證研究。針對(duì)工業(yè)環(huán)境復(fù)雜所導(dǎo)致采集的樣本數(shù)據(jù)性能較差問(wèn)題,基于本文提出的仿反饋認(rèn)知智能方法,研究了基于火焰圖像的工業(yè)回轉(zhuǎn)窯燒成狀態(tài)仿反饋認(rèn)知智能系統(tǒng)。選用東北大學(xué)流程工業(yè)綜合自動(dòng)化國(guó)家重點(diǎn)實(shí)驗(yàn)室提供的某水泥廠2#回轉(zhuǎn)窯燒成帶火焰圖像樣本和測(cè)量數(shù)據(jù),采用MATLAB仿真實(shí)驗(yàn)驗(yàn)證本方法的可行性與有效性。實(shí)驗(yàn)結(jié)果表明,本文方法能夠從宏觀到微觀挖掘火焰圖像特征知識(shí)并反復(fù)認(rèn)知決策面附近的樣本,為實(shí)現(xiàn)水泥燒結(jié)過(guò)程監(jiān)控和基于熟料質(zhì)量閉環(huán)控制的“機(jī)器看火”取代“人工看火”探索了一種工程應(yīng)用新方法。(7)多目標(biāo)不完全狀態(tài)的人體健康狀態(tài)評(píng)測(cè)的機(jī)器認(rèn)知應(yīng)用驗(yàn)證研究。針對(duì)人群樣本非均質(zhì)性、人體特征多樣性和人體特征值隨機(jī)性等問(wèn)題,基于本文提出的仿反饋認(rèn)知智能方法,研究了基于變認(rèn)知知識(shí)粒度的人體健康狀態(tài)仿反饋認(rèn)知智能系統(tǒng)。選用中國(guó)科學(xué)院智能機(jī)械研究所提供的隨機(jī)人群生物電阻抗信號(hào)樣本,采用MATLAB仿真實(shí)驗(yàn)以驗(yàn)證本方法的可行性與有效性。實(shí)驗(yàn)結(jié)果表明,本文方法能夠在不同認(rèn)知知識(shí)粒度層次中表征健康知識(shí)并模糊匹配健康指標(biāo),為客觀準(zhǔn)確地評(píng)測(cè)人體健康狀態(tài)的“機(jī)器診斷”取代“人工診斷”探索了一種實(shí)際應(yīng)用新方法。(8)單目標(biāo)不完全狀態(tài)的全天候光伏發(fā)電智能認(rèn)知跟蹤控制應(yīng)用驗(yàn)證研究。針對(duì)天氣環(huán)境的非線性、非平穩(wěn)性、大間歇性和隨機(jī)性導(dǎo)致的光伏電池跟蹤控制難題,基于本文提出的仿反饋認(rèn)知智能方法,研究了全天候光伏發(fā)電智能認(rèn)知跟蹤控制系統(tǒng),并給出了基于全景圖像變粒度仿反饋認(rèn)知太陽(yáng)位置的計(jì)算方法。采用平板型和聚光型等多種光伏電池組件及其伺服機(jī)構(gòu),開(kāi)展了實(shí)驗(yàn)研究以驗(yàn)證本文方法的可行性與有效性。實(shí)驗(yàn)結(jié)果表明,本文的三層三段光伏發(fā)電智能認(rèn)知跟蹤控制系統(tǒng)模型能夠基于風(fēng)、雪、白天、黑夜、陰/雨和晴/多云等環(huán)境與系統(tǒng)狀態(tài)的認(rèn)知知識(shí)執(zhí)行相應(yīng)的控制策略并在晴/多云跟蹤控制中基于準(zhǔn)確計(jì)算太陽(yáng)方位提高光伏效能,為實(shí)現(xiàn)光伏發(fā)電系統(tǒng)的高效、節(jié)能和安全運(yùn)行探索了一種智能化控制應(yīng)用新方法。
[Abstract]:To simulate human consciousness, the process of thinking is a very challenging science. In this paper, there is a significant difference in the information interaction between the one-way open loop mode of the traditional cognitive system and the comparison of the human cognitive things, and the difficult problem that the recognition rate and the correct rate can not be measured online in real time in the cognitive system, and the inaccuracy is discussed. Based on rough set theory, a model structure model and operation mechanism for establishing a cognitive object of uncertain information are explored based on rough set theory. Based on the generalized error theory and entropy theory, the multiple cognitive errors are explored. Based on the feedback control idea and the cognitive knowledge granularity computing tool, a cognitive intelligence operation mechanism with mimic feedback mode is established based on the feedback control idea and the cognitive knowledge granularity computing tool. The cognitive intelligence mechanism and the calculation model of the thinking information interaction model are compared. The main achievements of this paper are as follows: (1) research on the structure and operation mechanism of the imitative feedback cognitive intelligence system with uncertain information cognitive objects. The structure mode and operation mechanism of the three layer and three segment mutual coupling feedback cognitive intelligent system with repeated interaction mode are given, and the construction target of the imitation feedback cognitive intelligent system is given, the functional requirements and the operating mechanism are standardized, and the model structure is constructed for the imitation and recognition intelligent system of the uncertain information cognitive object. Method. (2) research on cognitive intelligence decision information system model of uncertain information cognitive object. Aiming at the problem that there is no common knowledge acquisition method that can adapt to all kinds of data in the current academic circle, the multi information fusion of uncertain information cognitive objects based on rough set is constructed and the intelligent decision information of supervised learning cognition is constructed. The system provides an index of cognitive knowledge fusion sufficiency and classification entropy function form based on characteristic simplicity. Under the uncertain information condition of finite domain, it provides a universal cognitive intelligence decision system model for the cognitive knowledge optimization representation of uncertain information cognitive objects. (3) the effect of uncertain cognitive process and Research on the generalized cognitive error evaluation system of cognitive results. In view of the fact that the current academic circles generally adopt the method of cognitive results reliability of posterior evaluation to meet the online real-time evaluation of recognition rate and correct rate in the cognitive system, the cognitive errors of uncertain information cognitive objects and uncertain cognitive process effects and cognitive results are constructed. The information system defines the uncertain cognitive process effect and the cognitive result error entropy based on the entropy function measure index. It does not determine the three generalized cognitive errors of the cognitive process effect and the cognitive result error entropy sequence and the cognitive knowledge granularity error, and establishes the online reality of the uncertainty recognition process effect and the cognitive result reliability. The time evaluation system provides a quantitative standard for the feedback cognitive intelligent adjustment mechanism. (4) the study of the imitating feedback cognitive intelligence mechanism of the uncertain information cognitive objects. The mimic feedback cognitive intelligence regulation mechanism which is poor online real-time measurement, defines the rules and calculation methods of the imitation feedback cognitive knowledge granularity, and establishes a multi-level variable knowledge granularity interlayer adjustment and the layer optimization model, and realizes the imitation feedback cognitive intelligent adjustment mechanism for the variable knowledge granularity of the uncertain information cognitive objects. Cognitive things provide an intelligent cognitive mechanism for the interactive process of information interaction. (5) the research and verification of the machine cognitive application of the off-line handwritten Chinese character image with a single goal and complete state. The recognition problem of the handwritten Chinese characters is large, the font font is numerous, the similar characters are many, and the writing style is different. The simulation feedback cognitive intelligence system of off-line handwritten Chinese character image with cognitive knowledge granularity intelligent adjustment mechanism is studied. The simulation experiment is carried out to verify the feasibility and effectiveness of this method by using the multi class Chinese character sample images of the SCUT-IRAC HCCLIB handwritten Chinese character image sample library as the cognitive object. The results show that this method has obvious advantages over the traditional one-way open loop method. A new practical application method is explored for the realization of "machine literacy" instead of "artificial literacy" for the off-line handwritten Chinese character image. (6) the machine cognitive application verification research on the burning state of industrial rotary kiln with multiple targets and complete state. Based on the imitation feedback cognitive intelligence method proposed in this paper, the imitation feedback cognitive intelligence system of the firing state of industrial rotary kiln based on flame image is studied based on the proposed simulation feedback cognitive intelligence method. The 2# rotary kiln firing zone of a cement plant is selected from the State Key Laboratory of the integrated automation of the process industry of Northeastern University. The flame image sample and the measured data are verified by MATLAB simulation experiment. The experimental results show that the method can excavate the characteristics of flame image from macro to micro and recognize the samples near the decision surface repeatedly, so as to realize the monitoring of the cement sintering process and the closed loop control of the clinker quality. A new method of engineering application is explored in place of "fire" instead of "fire". (7) a machine cognitive application verification study of human health status assessment of multi objective incomplete state. The imitation feedback cognitive intelligence system of human health state based on variable cognitive knowledge is studied. The feasibility and effectiveness of this method are verified by using MATLAB simulation experiments to verify the feasibility and effectiveness of this method. The results show that this method can be in different cognitive knowledge. To characterize health knowledge and fuzzy matching health indicators in the hierarchy of granularity, a new method is explored for the objective and accurate evaluation of human health status by "machine diagnosis" instead of "artificial diagnosis". (8) application verification research on intelligent recognition and tracking control of all weather photovoltaic power generation in single target incomplete state. The problem of photovoltaic cell tracking control is caused by nonlinear, non stationary, large intermittency and randomness. Based on the simulated feedback cognitive intelligence method proposed in this paper, the intelligent cognitive tracking control system for all weather photovoltaic power generation is studied, and a calculation method based on panoramic image variable granularity feedback is given. The experimental research is carried out to verify the feasibility and effectiveness of this method. The experimental results show that the model of the intelligent cognitive tracking control system of three layers and three segments of photovoltaic power generation can be based on the environment and system state of wind, snow, day, night, cloudy / rain and cloudy / cloudy. The cognitive knowledge carries out the corresponding control strategy and improves the photovoltaic efficiency based on the accurate calculation of the sun azimuth in the clear / multi cloud tracking control. A new intelligent control application method is explored to realize the high efficiency, energy saving and safe operation of the photovoltaic power generation system.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP18

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