Grid integration of wind power is essential to reduce fossil fuel usage but challenging in view of the intermittent nature of wind.Recently,we developed a hybrid Markovian and interval approach for the unit commitment...Grid integration of wind power is essential to reduce fossil fuel usage but challenging in view of the intermittent nature of wind.Recently,we developed a hybrid Markovian and interval approach for the unit commitment and economic dispatch problem where power generation of conventional units is linked to local wind states to dampen the effects of wind uncertainties.Also,to reduce complexity,extreme and expected states are considered as interval modeling.Although this approach is effective,the fact that major wind farms are often located in remote locations and not accompanied by conventional units leads to conservative results.Furthermore,weights of extreme and expected states in the objective function are difficult to tune,resulting in significant differences between optimization and simulation costs.In this paper,each remote wind farm is paired with a conventional unit to dampen the effects of wind uncertainties without using expensive utility-scaled battery storage,and extra constraints are innovatively established to model pairing.Additionally,proper weights are derived through a novel quadratic fit of cost functions.The problem is solved by using a creative integration of our recent surrogate Lagrangian relaxation and branch-and-cut.Results demonstrate modeling accuracy,computational efficiency,and significant reduction of conservativeness of the previous approach.展开更多
During efficiency evaluating by DEA, the inputs and outputs of DMUs may be intervals because of insufficient information or measure error. For this reason, interval DEA is proposed. To make the efficiency scores more ...During efficiency evaluating by DEA, the inputs and outputs of DMUs may be intervals because of insufficient information or measure error. For this reason, interval DEA is proposed. To make the efficiency scores more discriminative, this paper builds an Interval Modified DEA (IMDEA) model based on MDEA. Furthermore, models of obtaining upper and lower bounds of the efficiency scores for each DMU are set up. Based on this, the DMUs are classified into three types. Next, a new order relation between intervals which can express the DM’s preference to the three types is proposed. As a result, a full and more convictive ranking is made on all the DMUs. Finally an example is given.展开更多
In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable...In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.展开更多
Multitarget stool DNA(mt-sDNA) testing was approved for average risk colorectal cancer(CRC) screening by the United States Food and Drug Administration and thereafter reimbursed for use by the Medicare program(2014).T...Multitarget stool DNA(mt-sDNA) testing was approved for average risk colorectal cancer(CRC) screening by the United States Food and Drug Administration and thereafter reimbursed for use by the Medicare program(2014).The United States Preventive Services Task Force(USPSTF) October 2015 draft recommendation for CRC screening included mt-s DNA as an "alternative" screening test that "may be useful in select clinical circumstances",despite its very high sensitivity for early stage CRC.The evidence supporting mt-s DNA for routine screening use is robust.The clinical efficacy of mt-s DNA as measured by sensitivity,specificity,life-years gained(LYG),and CRC deaths averted is similar to or exceeds that of the other more specifically recommended screening options included in the draft document,especially those requiring annual testing adherence.In a population with primarily irregular screening participation,tests with the highest point sensitivity and reasonable specificity are more likely to favorably impact CRC related morbidity and mortality than those depending on annual adherence.This paper reviews the evidence supporting mt-s DNA for routine screening and demonstrates,using USPSTF's modeling data,that mt-s DNA at three-year intervals provides significant clinical net benefits and fewer complications per LYG than annual fecal immunochemical testing,high sensitivity guaiac based fecal occult blood testing and 10-year colonoscopy screening.展开更多
This paper shows that, for every unit interval graph, there is a labelling which is simultaneously optimal for the following seven graph labelling problems: bandwidth, cyclic bandwidth, profile, fill-in, cutwidth, mod...This paper shows that, for every unit interval graph, there is a labelling which is simultaneously optimal for the following seven graph labelling problems: bandwidth, cyclic bandwidth, profile, fill-in, cutwidth, modified cutwidth, and bandwidth sum(linear arrangement).展开更多
针对目前团购推荐方法较少结合单个用户与群组用户,并且对时间间隔、社交关系等上下文相关信息的利用不充分的问题,提出了一种基于社交关系和时序信息的团购推荐方法。对单个用户进行推荐时,针对循环神经网络(RNN)的门控循环单元(GRU)...针对目前团购推荐方法较少结合单个用户与群组用户,并且对时间间隔、社交关系等上下文相关信息的利用不充分的问题,提出了一种基于社交关系和时序信息的团购推荐方法。对单个用户进行推荐时,针对循环神经网络(RNN)的门控循环单元(GRU)在团购推荐时没有考虑时序信息的影响,以及用户-商品交互序列中不相关的商品数据会产生噪声等问题,提出了融合时序感知GRU和自注意力的团购推荐模型(RTSA)。首先,通过计算用户购买的任意两个商品之间的个性化时间间隔,构建了时序感知GRU(TGRU)模型;然后,采用自注意力网络研究商品位置及个性化时间间隔的影响;最后,实验结果表明在Amazon Beauty数据集中,RTSA相较于对单个用户推荐的最优的基线模型——基于时间间隔感知自注意力的序列化推荐模型(TiSASRec),前10个商品命中率提升了11.73%。对群组用户进行推荐时,针对团购群组推荐中预定义的融合策略不能动态获取群组用户权重,以及群组-项目交互数据的稀疏性等问题,提出了融合社交网络和分层自注意力的团购推荐模型(SSAGR)。首先,采用RNN捕捉团购中用户随时间变化的复杂潜在兴趣;其次,利用分层自注意力网络将社交网络信息整合到用户表示中,在不同权重下实现群组偏好聚合策略;然后,通过神经协同过滤(NCF)挖掘群组-项目交互,并实现了团购推荐;最后,实验结果表明,在MaFengWo数据集中,SSAGR相较于对群组用户推荐的最优的基线模型AGREE(Attentive Group REcommEndation),前5个商品命中率提升了3.53%。展开更多
<正> This paper introduces the theory of continuous lattices to the study of the Hutton unit interval I(L). some theorems related to I(L) are pithily proved. A kind of intrinsic topologies is applied to refining...<正> This paper introduces the theory of continuous lattices to the study of the Hutton unit interval I(L). some theorems related to I(L) are pithily proved. A kind of intrinsic topologies is applied to refining the topology of I(L),and a new fuzzy unit interval,called the H(λ) unit interval,is defined.Based on the H(λ) unit interval the H(λ)-complete regularity is introduced.Also,the theory of. H(λ)-stone-ech compactifications is established展开更多
JUST like in classical mathematics, fuzzy unit interval I(L) and fuzzy real line R(L), thebasic and important research objects of fuzzy mathematics, also interest a good few scholars.In 1992, Wang and Xu, by refining ...JUST like in classical mathematics, fuzzy unit interval I(L) and fuzzy real line R(L), thebasic and important research objects of fuzzy mathematics, also interest a good few scholars.In 1992, Wang and Xu, by refining the topology of I(L), defined a new fuzzy unit in-terval——H(λ) unit interval I(L), and established the Stone-Cech compactification theoryfor weakly induced L-fuzzy topological spaces. In 1993, Zhang and Liu introduced the con-cept of weak inducification of L-fuzzy topological space, and in this way, I(L) is exactly展开更多
基金supported in part by the Project Funded by ABB and U.S.National Science Foundation(ECCS-1509666)
文摘Grid integration of wind power is essential to reduce fossil fuel usage but challenging in view of the intermittent nature of wind.Recently,we developed a hybrid Markovian and interval approach for the unit commitment and economic dispatch problem where power generation of conventional units is linked to local wind states to dampen the effects of wind uncertainties.Also,to reduce complexity,extreme and expected states are considered as interval modeling.Although this approach is effective,the fact that major wind farms are often located in remote locations and not accompanied by conventional units leads to conservative results.Furthermore,weights of extreme and expected states in the objective function are difficult to tune,resulting in significant differences between optimization and simulation costs.In this paper,each remote wind farm is paired with a conventional unit to dampen the effects of wind uncertainties without using expensive utility-scaled battery storage,and extra constraints are innovatively established to model pairing.Additionally,proper weights are derived through a novel quadratic fit of cost functions.The problem is solved by using a creative integration of our recent surrogate Lagrangian relaxation and branch-and-cut.Results demonstrate modeling accuracy,computational efficiency,and significant reduction of conservativeness of the previous approach.
文摘During efficiency evaluating by DEA, the inputs and outputs of DMUs may be intervals because of insufficient information or measure error. For this reason, interval DEA is proposed. To make the efficiency scores more discriminative, this paper builds an Interval Modified DEA (IMDEA) model based on MDEA. Furthermore, models of obtaining upper and lower bounds of the efficiency scores for each DMU are set up. Based on this, the DMUs are classified into three types. Next, a new order relation between intervals which can express the DM’s preference to the three types is proposed. As a result, a full and more convictive ranking is made on all the DMUs. Finally an example is given.
基金State Grid Jiangsu Electric Power Co.,Ltd(JF2020001)National Key Technology R&D Program of China(2017YFB0903300)State Grid Corporation of China(521OEF17001C).
文摘In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.
文摘Multitarget stool DNA(mt-sDNA) testing was approved for average risk colorectal cancer(CRC) screening by the United States Food and Drug Administration and thereafter reimbursed for use by the Medicare program(2014).The United States Preventive Services Task Force(USPSTF) October 2015 draft recommendation for CRC screening included mt-s DNA as an "alternative" screening test that "may be useful in select clinical circumstances",despite its very high sensitivity for early stage CRC.The evidence supporting mt-s DNA for routine screening use is robust.The clinical efficacy of mt-s DNA as measured by sensitivity,specificity,life-years gained(LYG),and CRC deaths averted is similar to or exceeds that of the other more specifically recommended screening options included in the draft document,especially those requiring annual testing adherence.In a population with primarily irregular screening participation,tests with the highest point sensitivity and reasonable specificity are more likely to favorably impact CRC related morbidity and mortality than those depending on annual adherence.This paper reviews the evidence supporting mt-s DNA for routine screening and demonstrates,using USPSTF's modeling data,that mt-s DNA at three-year intervals provides significant clinical net benefits and fewer complications per LYG than annual fecal immunochemical testing,high sensitivity guaiac based fecal occult blood testing and 10-year colonoscopy screening.
文摘This paper shows that, for every unit interval graph, there is a labelling which is simultaneously optimal for the following seven graph labelling problems: bandwidth, cyclic bandwidth, profile, fill-in, cutwidth, modified cutwidth, and bandwidth sum(linear arrangement).
文摘针对目前团购推荐方法较少结合单个用户与群组用户,并且对时间间隔、社交关系等上下文相关信息的利用不充分的问题,提出了一种基于社交关系和时序信息的团购推荐方法。对单个用户进行推荐时,针对循环神经网络(RNN)的门控循环单元(GRU)在团购推荐时没有考虑时序信息的影响,以及用户-商品交互序列中不相关的商品数据会产生噪声等问题,提出了融合时序感知GRU和自注意力的团购推荐模型(RTSA)。首先,通过计算用户购买的任意两个商品之间的个性化时间间隔,构建了时序感知GRU(TGRU)模型;然后,采用自注意力网络研究商品位置及个性化时间间隔的影响;最后,实验结果表明在Amazon Beauty数据集中,RTSA相较于对单个用户推荐的最优的基线模型——基于时间间隔感知自注意力的序列化推荐模型(TiSASRec),前10个商品命中率提升了11.73%。对群组用户进行推荐时,针对团购群组推荐中预定义的融合策略不能动态获取群组用户权重,以及群组-项目交互数据的稀疏性等问题,提出了融合社交网络和分层自注意力的团购推荐模型(SSAGR)。首先,采用RNN捕捉团购中用户随时间变化的复杂潜在兴趣;其次,利用分层自注意力网络将社交网络信息整合到用户表示中,在不同权重下实现群组偏好聚合策略;然后,通过神经协同过滤(NCF)挖掘群组-项目交互,并实现了团购推荐;最后,实验结果表明,在MaFengWo数据集中,SSAGR相较于对群组用户推荐的最优的基线模型AGREE(Attentive Group REcommEndation),前5个商品命中率提升了3.53%。
基金Project supported by the National Natural Science Foundation of China
文摘<正> This paper introduces the theory of continuous lattices to the study of the Hutton unit interval I(L). some theorems related to I(L) are pithily proved. A kind of intrinsic topologies is applied to refining the topology of I(L),and a new fuzzy unit interval,called the H(λ) unit interval,is defined.Based on the H(λ) unit interval the H(λ)-complete regularity is introduced.Also,the theory of. H(λ)-stone-ech compactifications is established
文摘JUST like in classical mathematics, fuzzy unit interval I(L) and fuzzy real line R(L), thebasic and important research objects of fuzzy mathematics, also interest a good few scholars.In 1992, Wang and Xu, by refining the topology of I(L), defined a new fuzzy unit in-terval——H(λ) unit interval I(L), and established the Stone-Cech compactification theoryfor weakly induced L-fuzzy topological spaces. In 1993, Zhang and Liu introduced the con-cept of weak inducification of L-fuzzy topological space, and in this way, I(L) is exactly
