Patents
Literature
7 results about "Uncertain data" patented technology
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
In computer science, uncertain data is data that contains noise that makes it deviate from the correct, intended or original values. In the age of big data, uncertainty or data veracity is one of the defining characteristics of data. Data is constantly growing in volume, variety, velocity and uncertainty (1/veracity). Uncertain data is found in abundance today on the web, in sensor networks, within enterprises both in their structured and unstructured sources. For example, there may be uncertainty regarding the address of a customer in an enterprise dataset, or the temperature readings captured by a sensor due to aging of the sensor. In 2012 IBM called out managing uncertain data at scale in its global technology outlook report that presents a comprehensive analysis looking three to ten years into the future seeking to identify significant, disruptive technologies that will change the world. In order to make confident business decisions based on real-world data, analyses must necessarily account for many different kinds of uncertainty present in very large amounts of data. Analyses based on uncertain data will have an effect on the quality of subsequent decisions, so the degree and types of inaccuracies in this uncertain data cannot be ignored.
A dynamic scheduling method for uncertain data-intensive workflow in cloud environment
The application provides a dynamic scheduling method for uncertain data-intensive workflow in a cloud environment, solves the scheduling problem caused by the lack of transmission data size information, and helps to simultaneously reduce the cross-data center data transmission amount of the workflow and the execution cost of the workflow. First, the workflow structure is abstracted to obtain a DAG graph; then, static task pre-allocation is performed under the condition of partial data size information missing, an executable task forest graph of each data center is obtained, each task node in the forest graph is sorted according to the saved transmission data size, the task node with the largest saved data transmission size is allocated in the corresponding data center, and the predecessor node and the successor node of the node in the data center are also allocated in the data center, until all tasks are pre-allocated; then, dynamic adjustment of task allocation is performed based on the static task pre-allocation result and the actual transmission data size generated after the execution of each task in the workflow, and finally, an allocation scheme is obtained.
Owner:NANJING UNIV OF POSTS & TELECOMM
Method for determining the recruitment process of pilots using artificial intelligence based fuzzy multi-criteria decision making models
PCT designated stageWO2026135644A1Mathematical modelsData processing applicationsMathematical modelEngineering
The invention relates to a method for determining the recruitment process of pilots using artificial intelligence-based fuzzy multi-criteria decision-making models, which creates an artificial intelligence-based decision-making model by considering numerous criteria such as socio-cognitive abilities, performance competencies, communication skills, visual perspective perception, and spatial working range in the selection process of airline pilots; processes and evaluates uncertain, vague, and subjective data with fuzzy logic techniques (fuzzy TOPSIS, fuzzy VIKOR, and fuzzy PROMETHEE) and enables the ranking of candidates; transforms non-numerical linguistic terms into fuzzy mathematical models; ensures the integration of qualitative and quantitative data and the transformation of uncertain data into reliable results in pilot selections; facilitates the successful ranking of candidate pilots and the selection of competent personnel for safe operations by companies; improves the recruitment process of pilots and utilizes an artificial intelligence-based decision-making model application in their selection
Owner:İSTANBUL TEKNİK ÜNİVERSİTESİ BİLİMSEL ARARŞTIRMA PROJE BİRİM
A multi-agent game method considering uncertainty of data center demand response adjustment capability
The present application relates to the technical field of data center demand response, solves the technical problem of uncertain data center load regulation capacity, and particularly relates to a multi-agent game method considering uncertain data center demand response regulation capacity, comprising: constructing a data center user load optimization model; solving a microgrid operator optimization model to obtain a microgrid operator optimization strategy, and solving a non-data center user load optimization model to obtain a non-data center user load optimization strategy; inputting the non-data center user optimization strategy and the microgrid optimization strategy into the data center user load model for solving. The present application supports the participation of data centers in demand response through demand side resources of microgrid parks and non-data center user load regulation, solves the problem of uncertain data center load regulation capacity, thereby improving the flexibility of the power system, ensuring the safe and stable operation of the power system, and promoting renewable energy power consumption.
Owner:ELECTRIC POWER RES INST CHINA SOUTHERN POWER GRID CO LTD
Method and system for path optimization and operation mode adjustment of important user power supply
This invention provides a method and system for path optimization and operation mode adjustment for ensuring power supply to critical users, relating to the field of resource planning and allocation technology. By constructing a complete technical closed loop from multi-dimensional risk perception and dynamic hierarchical attribution to adaptive robust optimization, it provides a method for path optimization and operation mode adjustment that improves the accuracy, interpretability, and system robustness of power supply guarantee decisions for critical users. Through precise risk tracing, it achieves a shift from passive response to proactive elimination of risk root causes, improving the transparency and traceability of decision-making. By introducing dynamic risk transmission factors, it makes risk assessment results closer to the physical reality of the power grid, enhancing the accuracy of decision-making. Through adaptive multi-objective fusion optimization, it enhances the stability and reliability of the decision-making system under complex operating conditions and uncertain data environments.
Owner:STATE GRID BEIJING ELECTRIC POWER CO
A method for joint optimization of synthetic and conversion rate prediction of drug chemical reactions
ActiveCN115831246BChemical processes analysis/designNeural learning methodsChemical reactionPharmaceutical drug
The application discloses a kind of medicine chemical reaction synthesis and conversion rate prediction combined optimization method, comprising: obtaining the SMILES expression of reactant, the SMILES expression of reactant is tokenized, and the tokenization feature of the SMILES expression of reactant is obtained by embedding expression;The tokenization feature of the SMILES expression of reactant is hierarchically sequentially encoded;Chemical reaction synthesis prediction and conversion rate prediction two tasks are combined, and two tasks are trained simultaneously to realize chemical reaction synthesis and conversion rate prediction combined optimization.The application combines chemical reaction synthesis prediction and conversion rate prediction two tasks, introduces hierarchical sequence modeling technology, and the model interpretability parameter optimization of two tasks guides each other, to improve the training efficiency and performance of model.The application introduces uncertainty estimation to cope with the interference brought by model to uncertain data in real situation.
Owner:UNIV OF SCI & TECH BEIJING
A high-availability big data stream processing request placement method in a serverless edge network
The application belongs to the technical field of network services, and discloses a high-availability big data stream processing request placement method in a serverless edge network. The purpose is to meet the reliability requirements of users while minimizing processing delay. An effective algorithm is designed to find a suitable number of instances for the function of each data stream processing request, and to place the request while minimizing the average delay experienced by each user while meeting its reliability requirements. After the request is placed, the input data rate may change and is uncertain. An online learning algorithm is designed to predict the method to predict the data rate and dynamically adjust the standby instances to absorb the uncertain data rate. Based on the experiment of a real data set, it is shown that the placement problem of big data stream processing in the edge serverless network is effectively solved.
Owner:DALIAN UNIV OF TECH
A method for integrated management and intelligent rendering of multi-source geological map data
PendingCN122087017A2D-image generationGeographical information databasesMulti source dataKnowledge graph
This invention belongs to the field of artificial intelligence technology and discloses a method for integrated management and intelligent rendering of multi-source geological map data. This invention utilizes a multi-hypothesis generation method to proactively generate multiple competing but all reasonable geological interpretation schemes for areas with uncertain data, leveraging generative AI and geological knowledge graphs. Subsequently, through an interactive interpretive rendering mode, when a user queries geological elements in any scheme, the system can dynamically redraw the map, highlighting key evidence, darkening irrelevant backgrounds, and linking knowledge graph rules to visually reveal the AI's decision-making basis. This invention elevates AI mapping from an automated tool to an interactive and interpretable scientific verification partner, improving the scientific rigor and reliability of geological decision-making.
Owner:DEV RES CENT OF CHINA GEOLOGICAL SURVEY