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基于改进差分进化的最优化测井解释技术
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作者 张庆国 张雷 +1 位作者 李丹 葛云龙 《能源与环保》 2017年第6期44-47,共4页
最优化测井解释技术的发展,弥补了常规方法的局限性。尤其是在油气勘探逐渐向复杂储层上发展时,最优化测井解释可以综合利用多种信息的优势越发明显。基于对差分进化算法的改进进行最优化测井解释,尤其是针对其早熟与适用于无约束条件... 最优化测井解释技术的发展,弥补了常规方法的局限性。尤其是在油气勘探逐渐向复杂储层上发展时,最优化测井解释可以综合利用多种信息的优势越发明显。基于对差分进化算法的改进进行最优化测井解释,尤其是针对其早熟与适用于无约束条件下寻优等缺点,采取复合型算法生成子代来避免早熟,又加入alpha约束来进行有约束条件下的寻优。在进行测井解释时,分析区域岩性,选取测井特征明显的测井系列确定体积模型,可以利用重构测井曲线进行自检验,并且可以结合取心资料进行验证。 展开更多
关键词 改进差分进化 最优化测井解释 alpha约束 复合型算法 单纯型扩张算法
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An Overview and Perspectives On Bidirectional Intelligence: Lmser Duality, Double IA Harmony,and Causal Computation 被引量:3
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作者 Lei Xu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2019年第4期865-893,共29页
Advances on bidirectional intelligence are overviewed along three threads,with extensions and new perspectives.The first thread is about bidirectional learning architecture,exploring five dualities that enable Lmser s... Advances on bidirectional intelligence are overviewed along three threads,with extensions and new perspectives.The first thread is about bidirectional learning architecture,exploring five dualities that enable Lmser six cognitive functions and provide new perspectives on which a lot of extensions and particularlly flexible Lmser are proposed.Interestingly,either or two of these dualities actually takes an important role in recent models such as U-net,ResNet,and Dense Net.The second thread is about bidirectional learning principles unified by best yIng-yAng(IA)harmony in BYY system.After getting insights on deep bidirectional learning from a bird-viewing on existing typical learning principles from one or both of the inward and outward directions,maximum likelihood,variational principle,and several other learning principles are summarised as exemplars of the BYY learning,with new perspectives on advanced topics.The third thread further proceeds to deep bidirectional intelligence,driven by long term dynamics(LTD)for parameter learning and short term dynamics(STD)for image thinking and rational thinking in harmony.Image thinking deals with information flow of continuously valued arrays and especially image sequence,as if thinking was displayed in the real world,exemplified by the flow from inward encoding/cognition to outward reconstruction/transformation performed in Lmser learning and BYY learning.In contrast,rational thinking handles symbolic strings or discretely valued vectors,performing uncertainty reasoning and problem solving.In particular,a general thesis is proposed for bidirectional intelligence,featured by BYY intelligence potential theory(BYY-IPT)and nine essential dualities in architecture,fundamentals,and implementation,respectively.Then,problems of combinatorial solving and uncertainty reasoning are investigated from this BYY IPT perspective.First,variants and extensions are suggested for AlphaGoZero like searching tasks,such as traveling salesman problem(TSP)and attributed graph matching(AGM)that are turned into Go like problems with help of a feature enrichment technique.Second,reasoning activities are summarized under guidance of BYY IPT from the aspects of constraint satisfaction,uncertainty propagation,and path or tree searching.Particularly,causal potential theory is proposed for discovering causal direction,with two roads developed for its implementation. 展开更多
关键词 Autoencoder LMSER DUALITY outward attention associative recall concept formation imagining pattern transformation STD vs LTD RPCL skip connection feedback variational least redundancy Bayesian Ying Yang IA system best HARMONY best matching image THINKING rational THINKING INTELLIGENCE potential theory alpha-TSP alpha-AGM graph matching ME Player BYY Follower constraint satisfaction CAUSAL potential theory
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