Electricity meter area identification technology based on channel coding theory by Yinghai XIE, Yu ZHANG

“…Station area identification has always been a problem in the ubiquitous power Internet of things, a new analytical model similar to fading channel was established for the station area identification, and based on the remote on-load voltage regulation function of on-load capacity and voltage regulation distribution transformer, the channel coding theory was applied to solve the problem.In order to identify station area of the smart meters, different special voltage regulation schemes with the properties of repeated coding and block coding were applied synchronously.At the same time, the power consumption information acquisition system was used to collect the voltage of each smart meter in this period.Finally, the recognition of each meter was realized based on the principle of minimum distance of decoding algorithm.The theoretical analysis and test results show that, compared with the traditional technology, the new technology can realize the high accuracy identification of a large number of meters in the on-load capacity and voltage regulation distribution transformer area in the existing power grid system without upgrading, which has high engineering application value.…”
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Pricing of American Carbon Emission Derivatives and Numerical Method under the Mixed Fractional Brownian Motion by Yuling Wang, Jing Wang

“…In addition, we introduced a nonuniform grid-based modification of the fitted finite volume method for numerical solution. …”
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Focal Mechanisms of Mw 6.3 Aftershocks from Waveform Inversions, Phayao Fault Zone, Northern Thailand by Kasemsak Saetang

“…Source positions were created by using a single-source inversion and a grid-search method computed to optimize the waveform match. …”
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Component library creation and pixel array generation with micromilled droplet microfluidics by David McIntyre, Diana Arguijo, Kaede Kawata, Douglas Densmore

“…To show its ability to perform multistep workflows, these components were used to assemble droplet “pixel" arrays, where droplets were generated, sensed, sorted, and anchored onto a grid to produce images.…”
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De la teoría del lugar a la teoría del paisaje: no-lugar, distalidad y carácter by Pascual Riesco Chueca

“…Dicha matriz, libremente inspirada en la teoría cultural “grid-group”, distingue cuatro tipos de paisaje. Un objeto del presente artículo es aclarar la posible ubicación de lugar y no-lugar dentro de la citada matriz. …”
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Study of the Effect of Centrifugal Force on Rotor Blade Icing Process by Zhengzhi Wang, Chunling Zhu

“…A numerical simulation method of three-dimensional rotor blade icing is presented. Body-fitted grids around the rotor blade are generated using overlapping grid technology and rotor flow field characteristics are obtained by solving N-S equations. …”
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Recurrent Fourier-Kolmogorov Arnold Networks for photovoltaic power forecasting by Desheng Rong, Zhongbao Lin, Guomin Xie

“…The results indicate that RFKAN achieves the best forecasting performance with a grid depth of 100 and an input sequence length of 2, reducing RMSE and MAE by at least 5%, increasing CORR by 2%, and decreasing training time by 24% compared to advanced models.…”
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Methodical and hardware-software for recording and processing speech signals for diagnosis of neurological diseases by T. P. Kul, M. M. Mezhennaya, Yu. N. Rushkevich, A. N. Osipov, S. A. Likhachev, I. V. Rushkevich

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Research on Shortest Path Planning and Smoothing Without Obstacle Collision Based on Moving Carrier by Lingsong Di, Defeng Sun, Yahui Qi, Zhicai Xiao

“…In response to the challenges of path planning in complex scenarios, to overcome the influence of optimal path determination by the precision of grid map sizes, and to escape the uncertainty in solving by intelligent algorithms, this paper designs a method for obtaining an adjacency matrix based on node planning of shortest path diagrams with polygonal obstacles and then uses the Dijkstra algorithm to get the shortest path. …”
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Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model by Hui Chen, Shenghua Xiong, Xuan Ren

“…A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.…”
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Algorithms for partitioning logical circuits into subcircuits by N. A. Kirienko

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Methodology for Assessing the Probability of Corrosion in Concrete Structures on the Basis of Half-Cell Potential and Concrete Resistivity Measurements by Lukasz Sadowski

“…Potential Ecorr and concrete resistivity ρ in each point of the applied grid were measured. The experimental results indicate that the proposed methodology can be successfully used to assess the probability of corrosion in concrete structures.…”
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A Novel Prediction Method of Dynamic Wall Pressure for Silos Based on Support Vector Machine by Hanhua Yu, Zhijun Xu, Tingting Liu, Fang Yuan

“…Considering the nonlinear relationship between the factors which affect the dynamic lateral pressure of silos, a prediction method of dynamic wall pressure for silos based on support vector machine (SVM) is proposed here, and furthermore, the modified grid search method (GSM) is incorporated in obtaining the optimal support vector machine parameters to improve the accuracy of the prediction. …”
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Multiobjective Particle Swarm Optimization Based on Ideal Distance by Shihua Wang, Yanmin Liu, Kangge Zou, Nana Li, Yaowei Wu

“…In IDMOPSO, the adaptive grid and ideal distance are used to optimize and improve the selection method of global learning samples and the size control strategy of the external archive, and the fine-tuning parameters are introduced to adjust particle flight in the swarm dynamically. …”
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Geospatial Trends and Decadal Anomalies in Extreme Rainfall over Uganda, East Africa by Charles Onyutha

“…The data were extracted from high-resolution (0.5° × 0.5°) gridded daily series of the Princeton Global Forcings covering the period 1948–2008. …”
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Processus de gestion des ressources éducatives. Le cas d’enseignants en IUT by Cécile Redondo, Rémi Cadet, Romain Perrier, Béatrice Drot-Delange

“…Taking as our starting point the characterization of processes already identified among teachers in technological secondary education, we identify, through the analysis of semi-structured interviews, four processes at work among the teachers: transmission-inheritance, collection of resources, constitution of a network of trust, i.e. recognition of the reliability and/or relevance of a resource, and participation in resource-producing collectives. A coding grid for the interviews is established, with the semantic unit as the chosen coding unit. …”
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ARSS: A Novel Aerial Robot Performs Tree Pruning Tasks by Hao Xu, Zhong Yang, Le Chang, Kaiwen Lu, Changliang Xu, Qiuyan Zhang

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Nonexposure Accurate Location K-Anonymity Algorithm in LBS by Jinying Jia, Fengli Zhang

“…They are designed for K-anonymity, and cloaking is performed based on the identifications (IDs) of the grid areas which were reported by all the users, instead of directly on their accurate coordinates. …”
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Systematic Thinking and Evaluation of Construction Quality Management Standardization of Power Engineering in China by Tai-Ping Yuan, Jing-Feng Ou, Juan Wang, Wei Zhang

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A big data framework for short-term power load forecasting using heterogenous data by Haibo ZHAO, Zhijun XIANG, Linsong XIAO

“…The power system is in a transition towards a more intelligent, flexible and interactive system with higher penetration of renewable energy generation, load forecasting, especially short-term load forecasting for individual electric customers plays an increasingly essential role in future grid planning and operation.A big data framework for short-term power load forcasting using heterogenous was proposed, which collected the data from smart meters and weather forecast, pre-processed and loaded it into a NoSQL database that was capable to store and further processing large volumes of heterogeneous data.Then, a long short-term memory (LSTM) recurrent neural network was designed and implemented to determine the load profiles and forecast the electricity consumption for the residential community for the next 24 hours.The proposed framework was tested with a publicly available smart meter dataset of a residential community, of which LSTM’s performance was compared with two benchmark algorithms in terms of root mean square error and mean absolute percentage error, and its validity has been verified.…”
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