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1. 发明授权

EP4085257B1 SYSTEMS AND METHODS FOR IMPROVED AUTOMATION OF LABORATORY PROCESSES 有权
公开(公告)号：EP4085257B1
公开(公告)日：2024-07-10
申请号：EP20851296.2
申请日：2020-12-29
IPC分类号： G01N35/00 , G06N3/12 , G06F17/00
CPC分类号： G01N35/0092 , G01N2035/009420130101 , G06N3/126 , G06N5/01 , G06N7/01

2. 发明公开

EP3400557A1 WEBINTERFACE GENERATION AND TESTING USING ARTIFICIAL NEURAL NETWORKS 审中-公开
公开(公告)号：EP3400557A1
公开(公告)日：2018-11-14
申请号：EP17735903.1
申请日：2017-01-05
申请人： Sentient Technologies (Barbados) Limited
发明人： MIIKKULAINEN, Risto , ISCOE, Neil
IPC分类号： G06N3/02 , G06N5/00 , G06N3/12 , G06F17/30
CPC分类号： G06N3/04 , G06F3/0484 , G06F8/36 , G06F9/451 , G06F11/3664 , G06F17/2247 , G06F17/30377 , G06F17/30572 , G06F17/3089 , G06N3/086 , G06N3/126
摘要： Roughly described, the technology disclosed provides a so-called machine-learned conversion optimization (MLCO) system that uses artificial neural networks and evolutionary computations to efficiently identify most successful webpage designs in a search space without testing all possible webpage designs in the search space. The search space is defined based on webpage designs provided by marketers. Neural networks are represented as genomes. Neural networks map user attributes from live user traffic to different dimensions and dimension values of output funnels that are presented to the users in real time. The genomes are subjected to evolutionary operations like initialization, testing, competition, and procreation to identify parent genomes that perform well and offspring genomes that are likely to perform well.

3. 发明公开

EP3316184A4 PROGRAM GENERATING DEVICE, PROGRAM GENERATING METHOD, AND GENERATING PROGRAM 有权
公开(公告)号：EP3316184A4
公开(公告)日：2018-07-18
申请号：EP15896359
申请日：2015-06-25
申请人： FUJITSU LTD
发明人： NAGATO TSUYOSHI , KOEZUKA TETSUO
IPC分类号： G06F8/36 , G06F9/44 , G06K9/00 , G06K9/62 , G06N3/12 , G06T5/20 , G06T7/00
CPC分类号： G06N3/126 , G06F8/36 , G06F9/44 , G06K9/00993 , G06K9/6202 , G06K9/6229 , G06K9/6256 , G06N3/12 , G06T5/20 , G06T7/00
摘要： To perform appropriate survival selectin when generating an image processing program by using genetic programming. A processing unit (1b) selects an image processing program (21) from among a plurality of image processing programs (21, 22, 23, and so on) each generated by combining a plurality of partial programs; generates an image processing program (21a) by changing a part of the partial programs included in the image processing program (21); performs image processing on an input image (11), using the image processing program (21a); determines whether to pass the image processing program (21a) to the next generation, based on a comparison between one or more intermediate output images (31 and 32) that are output halfway through the image processing and a first target image (12); and replaces one of the image processing programs (21, 22, 23, and so on) with the image processing program (21a) when the image processing program (21a) is determined to be passed to the next generation.

4. 发明公开

EP3161730A4 A SYSTEM AND METHOD FOR MODELLING SYSTEM BEHAVIOUR 无效
公开(公告)号：EP3161730A4
公开(公告)日：2018-02-28
申请号：EP15814757
申请日：2015-06-29
申请人： EVOLVING MACHINE INTELLIGENCE PTY LTD
发明人： GREENWOOD NIGEL JOHN CONRAD
IPC分类号： G06F19/12 , G16H50/50
CPC分类号： G06F17/5009 , G06F17/00 , G06F17/13 , G06F17/50 , G06F19/10 , G06N3/126 , G16H50/50
摘要： A method of modelling system behaviour of a physical system, the method including, in one or more electronic processing devices obtaining quantified system data measured for the physical system, the quantified system data being at least partially indicative of the system behaviour for at least a time period, forming at least one population of model units, each model unit including model parameters and at least part of a model, the model parameters being at least partially based on the quantified system data, each model including one or more mathematical equations for modelling system behaviour, for each model unit calculating at least one solution trajectory for at least part of the at least one time period; determining a fitness value based at least in part on the at least one solution trajectory; and, selecting a combination of model units using the fitness values of each model unit, the combination of model units representing a collective model that models the system behaviour.

5. 发明公开

EP3156897A1 PROGRAM GENERATION DEVICE, PROGRAM GENERATION METHOD AND PROGRAM 有权
标题翻译：程序生成装置，程序生成方法及程序
公开(公告)号：EP3156897A1
公开(公告)日：2017-04-19
申请号：EP14894688.2
申请日：2014-06-11
申请人： Fujitsu Limited
发明人： OKAMOTO, Hiroaki , NAGATO, Tsuyoshi , KOEZUKA, Tetsuo
IPC分类号： G06F9/44 , G06F11/36 , G06N3/00 , G06T1/00
CPC分类号： G06N3/126 , G06F8/36 , G06F9/44 , G06F11/36 , G06N3/00 , G06N7/005 , G06T1/00
摘要： Time needed to generate an image processing program is shortened.
Each time evolution processing is performed, an information recording unit (1b) records increase-decrease information (2a) indicating a type of partial program changed in number between pre- and post-evolution individuals and difference between fitness levels calculated from the pre- and post-evolution individuals in a storage unit (1d). A probability setting unit (1c) determines, per partial program, a contribution level indicating how much a partial program contributes to increasing a fitness level, based on the information (2a) stored in the storage unit (1d) within a predetermined period and sets a selection probability per partial program in such a manner that a partial program having a higher contribution level is given a higher selection probability. When the evolution processing is performed, a generation processing unit (1a) selects a partial program to be included in the post-evolution individual in mutation processing according to the set selection probabilities.

6. 发明授权

EP2296410B1 Telecommunications network node and methods 有权转让
标题翻译：电信网络节点和方法
公开(公告)号：EP2296410B1
公开(公告)日：2017-02-08
申请号：EP09360042.7
申请日：2009-09-10
申请人： ALCATEL LUCENT
发明人： Ho, Lester T.W. , Claussen, Holger
IPC分类号： G06N3/12 , H04W52/34 , H04W24/02
CPC分类号： H04W52/343 , G06N3/126 , H04W24/02 , H04W52/143 , H04W52/325 , H04W84/045

7. 发明授权

EP2345020B1 VERKEHRSADAPTIVE NETZSTEUERUNG UND VERFAHREN ZUR OPTIMIERUNG DER STEUERUNGSPARAMETER 有权转让
标题翻译：交通自适应网络控制和方法优化控制参数
公开(公告)号：EP2345020B1
公开(公告)日：2016-02-24
申请号：EP09783452.7
申请日：2009-09-28
申请人： PTV Planung Transport Verkehr AG
发明人： KEMPER, Carsten , BRAUN, Robert , MAIER, Peter , WEICHENMEIER, Florian
IPC分类号： G08G1/08 , G06N3/12 , G08G1/081
CPC分类号： G08G1/08 , G06N3/126 , G08G1/081

8. 发明公开

EP2880578A2 ESTIMATING REMAINING USEFUL LIFE FROM PROGNOSTIC FEATURES DISCOVERED USING GENETIC PROGRAMMING 审中-公开
标题翻译：剩余使用寿命估计遗传编程方法发现预后特征
公开(公告)号：EP2880578A2
公开(公告)日：2015-06-10
申请号：EP13752703.2
申请日：2013-07-26
申请人： Siemens Corporation
发明人： LIAO, Linxia , EDMONDSON, Zachery
IPC分类号： G06F19/28
CPC分类号： G01M99/00 , G01M13/00 , G05B23/0283 , G06N3/126
摘要： A method for estimating a remaining useful life of a system includes monitoring sensor data from sensors deployed within a system (S21). A plurality of features are extracted from the sensor data (S22). Tree graphs are generated including mathematical operators and features as nodes and a advanced feature is produced from each of the tree graphs by transforming the tree graphs into equations (S23). A recursive operation including analyzing a fitness of each of the advanced features (S24), performing crossover/mutation on the tree graphs (S26), producing advanced features from the altered tree graphs, and analyzing the fitness of the altered tree graphs to produce at least one final advanced feature is performed (S27). A remaining useful life of the system is calculated based on the final advanced feature (S29)

9. 发明公开

EP2872041A1 DEVICE TO DETERMINE DYSKINESIA 有权转让
标题翻译：设备技术测定运动障碍
公开(公告)号：EP2872041A1
公开(公告)日：2015-05-20
申请号：EP13741818.2
申请日：2013-07-15
申请人： The University Of York
发明人： SMITH, Stephen
IPC分类号： A61B5/11 , A61B5/00
CPC分类号： A61B5/1101 , A61B5/1114 , A61B5/4082 , A61B5/6831 , A61B5/7264 , A61B2505/07 , A61B2562/0219 , G06N3/126 , G16H50/20 , G16H50/70
摘要： The invention disclosed herein is to a device to assist in the determination of the presence and type of dyskinesia in a patient. The device includes a sensor, removably attachable to a patient's body, such as on a limb or torso, the sensor being capable of detecting 3-D motion. Data generated by the sensor is transferred to and retained in a data retention means. A processing means is included to process the generated data, along with a look-up table of processed data for already known dyskinesia conditions for comparison, The processing means employs an evolutionary algorithm in the classification of the data. Output means display the diagnosed condition to a user.

10. 发明公开

EP2863340A2 Distributed machine learning intelligence development systems 审中-公开
标题翻译：分布式机器学习智能开发系统
公开(公告)号：EP2863340A2
公开(公告)日：2015-04-22
申请号：EP14189068.1
申请日：2014-10-15
申请人： Lockheed Martin Corporation
发明人： Harrison, Gregory Anhony , Worden, Eric W. , Brant, Jonathan Charles , Smith, David A.
IPC分类号： G06N5/02
CPC分类号： G06N5/043 , G06N3/126
摘要： A system, method, and computer-readable instructions for a distributed machine learning system are provided. A plurality of distributed learning environments are in communication over a network, wherein each environment has a computing device having a memory and a processor coupled to the memory, the processor adapted implement a learning environment via one or more agents in a rules-based system, wherein the agents learn to perform tasks in their respective learning environment; and a persistent storage in which knowledge comprising a plurality of rules developed by the agents for performing the tasks are stored, wherein the knowledge is tagged and shared with other agents throughout the plurality of distributed learning environments.
摘要翻译：提供了用于分布式机器学习系统的系统，方法和计算机可读指令。多个分布式学习环境通过网络进行通信，其中每个环境具有计算设备，所述计算设备具有存储器和耦合到所述存储器的处理器，所述处理器适于通过基于规则的系统中的一个或多个代理实现学习环境，其中代理学习在其各自的学习环境中执行任务; 以及持久性存储器，其中存储包括由代理开发的用于执行任务的多个规则的知识，其中知识在整个多个分布式学习环境中被标记并与其他代理共享。

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