The tie-line power adjustment is an essential part of the power system operation state calculation. Various existing algorithms to solve the tie-line power adjustment problem are mainly implemented by introducing tie-...
The tie-line power adjustment is an essential part of the power system operation state calculation. Various existing algorithms to solve the tie-line power adjustment problem are mainly implemented by introducing tie-line power equation constraints into conventional power flow calculations. Such methods have low calculation efficiency, not enough automation, and are prone to non-convergence in the power flow calculation. In this paper, the tie-line power adjustment problem is formulated as a Markov decision process, and the proximal policy optimization algorithm is introduced to optimize the decision policy. In order to enhance the effectiveness of the proposed method, a new deep neural network structure suitable for the proximal policy optimization algorithm is designed. The proposed method is verified with the IEEE 39-bus system.
This paper proposes and improves a model for China's cotton reserves trading market, generates a more accurate price level table in contrast to the widely used China Cotton Association(CCA)'s table, and predic...
This paper proposes and improves a model for China's cotton reserves trading market, generates a more accurate price level table in contrast to the widely used China Cotton Association(CCA)'s table, and predicts the future trading price with this model. Data used is all 29895 trade records of cotton reserves from May, 2016 to Sept, 2016. In this paper, we firstly give a briefly introduction to the data as well as basic knowledge of cotton, especially the CCA's price level table as the target to improve accuracy. We then present a multiple linear regression with dummy variable model, which can reduce the error on predicting the trading price of current month, but still remains some problems such as the result shows a batch of cotton with better quality may get a lower price. So we finally advance the model with multidimensional isotonic regression and more factors taken into consideration. Our last model could be used to predict the trade price of both current month and next month with approximately 4% mean absolute percentage error(MAPE).
In this paper, the problem of training federated learning (FL) algorithms over a realistic wireless network is studied. In particular, in the considered model, wireless users execute an FL algorithm while training the...
详细信息
A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mits...
A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni
暂无评论