34 results about "Demand estimation" patented technology

Apparatus, systems and methods for service and / or business for coordinating tasks of performance management and application placement management in a dynamic fashion. An example process is dynamic in the face of fluctuations in the request load to the distributed computer system and the periodic adjustments to the placement of applications onto servers in said distributed computer system. There are two opposite functional flows in said process: a demand estimation function and a capacity adjustment function. The coordination system involves two subsystems: a demand estimator and a capacity adjuster, along with appropriate interfaces to of the performance manager and the application placement manager. This results in application placement process reacting quicker to demand fluctuations, performance guarantees are better met by rearranging the resources to be allocated to the various classes of service, and the management system works in an unsupervised mode, thus reducing manual administration costs and human errors.

The invention relates to a control method for refrigerator, concretely, it relates to control method for a frequency variable refrigerator, the invention provides a method for time division work of freezing chamber and cold storage chamber in the process of temperature control, and through the cold quantity demands estimation, the frosting process includes the refrigerating process of the cold storage chamber. The variable frequency refrigerator includes: primary CPU, freezing chamber, cold storage chamber, temperature sensor, compressor, the invention introduces the concepts of temperature change rate and target approaching rate, the refrigerator can adjust the temperature change of the refrigerator according to the rate.

A method and system can be used to determine an optimal price of a commodity on a spot market. Market state conditions can be generated using historical data, such as transactional and other data. The market state conditions may include nearly any number of attributes, and the forecast market state conditions may include a forecast price for the commodity during the next time period. The historical data and market state condition may be used in a clustering module that separates the data into clusters. The cluster with the market state condition is identified, and the data in that cluster is used to generate a price-demand curve for the next time period. The price for the commodity on the spot market during that time period can be determined consistent with the company's business rules.

The invention discloses a comprehensive traffic network operation situation detection simulation technology facing road and railway networks. The technology is characterized by comprising a regional comprehensive traffic and transportation network emergency simulation framework, a demand estimation and prediction model based on combination of trend prediction and a neural network and an agent-based multi-mode comprehensive transportation network simulation model. According to the comprehensive traffic network operation situation detection simulation technology facing the road and railway networks, by means of exiting road network and railway network traffic data, an overall framework of a regional comprehensive traffic and transportation network emergency simulation platform is constructed in a focused mode, a time-space network modeling technology is applied, and an agent-based multi-mode comprehensive traffic simulation model is constructed.

The application discloses a multi-mode travel O-D demand estimation method based on multi-source data check. The method comprises: S1, selecting basic elements in a transportation network and establishing an urban multi-mode transportation network model based on travel needs among the basic elements; and S2, carrying out pre-treatment on multi-source historical traffic data for checking an O-D demand estimator and carrying out statistic calculation to obtain needed basic data; and estimating the multi-mode O-D demand by using the model from the S1 and the calculation result from the S2 to obtain a novel total O-D demand. According to the method disclosed by the application, statistics is carried out based on multiple data sources; and he restriction on the previous single-mode O-D demand estimation is eliminated, the traffic characteristics of various modes of travel in the road network are considered comprehensively, the mutual feedback mechanism between O-D demands and section flowsis reflected, the problem of consistency between the O-D estimation value and the actual observation value is solved, and the obtained urban multi-mode O-D demand distribution result meets the user balance criteria.

The invention discloses an intelligent home energy management method based on social network behavior perception. The method comprises S101) acquiring user network social data and external environment data, S102) performing user network social behavior perception, S103) performing user environment demand estimation, S104) performing a user demand updating judgment, S105) performing event drive electrical appliance equipment control strategy optimization, and S106) updating a control strategy of a smart home control module according to a result of the step S105), and shifting to the step S101) to continuously monitor the user network social data. Through monitoring of user's network social software and mail management software, user network social behaviors are identified and predicted in real time, a demand of a user for home environment is estimated and updated, scheduling strategies of various kinds of electrical appliance equipment of smart home are made, the domestic electrical appliance equipment are actively controlled, a comfort requirement of the user for the home environment is satisfied, and electric cost is reduced at the same time.

The invention discloses a simulated annealing algorithm based traffic demand estimation method, belonging to the technical field of dynamic traffic distribution in traffic guidance systems. The method involves two calculation modes of a target function and result evaluation. A specific operation process comprises: (1) obtaining an optimal solution by utilizing a simulated annealing algorithm according to an initial seed; (2) obtaining partial information according to other information sources; and (3) calculating a result according to a confidence level, calculating the degree of confidence of the two modes according to an actual result, and updating the confidence level. The method has the beneficial effects that in view of the fact that an actual road network runs dynamically, a traffic dispatcher always can obtain initial information through a dispersed vehicle-mounted device or priori knowledge, so that a continuously changed OD matrix is estimated.

A configuration mapping system and method increase the effectiveness of mapping of information from an established product line to a new product offering. In at least one embodiment, the configuration mapping system herein uses configuration mapping rules to map individual product features and entire configurations from established products to a new product offering. The configuration mapping system also provides a way to appropriately map, for example, demand and sales information for the purpose of demand estimation and sales prediction. Conventionally, mapping can be ineffective because the configuration mapping rules usually focus on one part of the product at a time, and, if applied in isolation, the impact on other parts is missed. The systems and method herein provide a way to integrate configuration mapping rules across feature parts, time periods, and product lines into a unified, holistic view, allowing for new insights.

A future amount is created through demand estimation by rectifying data administrated in a logistics infrastructure through a system and a method for alternative simulation of a logistics infrastructure. In addition, an infrastructure load by a future year amount is analyzed and an alternative is selected through the load analysis.

The invention discloses a method which means when a wireless communication system carries out a video service, a combined application layer, a physical layer and a data link layer carries out cross-layer optimization to the video service. The method comprises the following steps that: a. when a video user initiates the video service, a video service server estimates demand bandwidth information of the user according to the demand of the video user; b. the video service server sends a message according to the estimated demand bandwidth information so as to notify a wireless resource management module of the system; c. the wireless resource management module schedules the physical layer so as to provide adaptive wireless resources for the video user according to the notification of the video service server. By using the method of the invention, the wireless communication system can effectively use the limited wireless resources to provide a service quality which satisfies the demand for the video user. The wireless resource wastes can be avoided. And the video user can adapt wireless link changes and baneful influences of the wireless link changes on the video service quality can be reduced. Therefore, the service quality obtained by the video user can be improved and user experiences can be improved too.

The invention belongs to the technical field of intelligent transportation control, relates to a signalized intersection traffic demand estimation method affected by a traffic stream, and is applicable to trunk lines and regional road systems. Various vehicle types and platoon dispersing characteristics are considered, intersection entrance stop lines and an upstream section of an intersection entrance, a plurality of traffic stream data sets are acquired, and platoon dispersing coefficient calibration method is provided based on the data sets, so that a traffic demand estimation model is built. Besides, technical application processes of the model and the method are given and explained by a use case according to computer programming software MATLAB and traffic simulation software VISSIM.The results show that a new method can accurately estimate signalized intersection lane group traffic demands according to traffic streams formed by various vehicle types.

The invention discloses a traffic demand estimation method based on GPS navigation data, a big data technology and an artificial intelligence algorithm are increasingly mature, the traffic informationacquisition cost is lower than that at any time in the past, and resident travel characteristics, space-time distribution characteristics of traffic demands and the like can be more intuitively and clearly understood. According to macroscopic data characteristics presented by big data, a hierarchical clustering algorithm is utilized to divide hot spot areas required by resident travel. Scientificand reasonable clustering division can analyze the travel demand of current residents, and an effective basis is provided for relieving urban traffic congestion and maximizing the utilization of traffic resources. The accurate estimation of the traffic demand can better understand the characteristics of urban traffic behaviors, provides a theoretical basis for urban traffic planning, effectivelyreduces the travel cost of residents, and improves the dispersion capability of urban emergencies.

A heat demand estimation device and method and a facility control device, method and system are provided (a heat demand estimation device, a heat demand estimation method, a facility control device, a facility control method, a facility control system, a control program, and a recording medium). The heat demand estimation device estimates heat demand of an air conditioning facility without installing a flow sensor. The heat demand estimation device includes: a data collection part (21) which obtains refrigeration machine electric power data from a refrigeration machine electric power sensor (5) which measures electrical power consumption of a refrigeration machine (43) of an air conditioning facility (4); and an estimated heat demand amount calculation part (22) which calculates an estimated heat demand amount from the electrical power consumption of the refrigeration machine (43) that is indicated by the refrigeration machine electric power data to output the estimated heat demand amount.

A passenger's activity at the normal entry and exit points to the transit system may be recorded and linked, using a transit ticking system, along with the passenger's transit time and onward travel mode (bike hire, taxi, etc.). These records can be linked to other parameters such as the time, day of the week, season of the year, weather, and / or other such parameters. Furthermore, the passenger may use the transit ticketing system to make onward travel reservations such a bike hire or taxi. Such reservations will also be linked with the entry and exit and other parameters. The passenger's entry and exit on subsequent visits may be recorded and aggregated with past travel parameters. Thus, when a user enters the transit system, the records for that user can be used to predict how long they may be in transit, where they may exit the transit system, and what type of onward travel they may use.

The invention belongs to the technical field of hotel management, and specifically relates to a demand curve estimation method in hotel yield management. The yield management aims at maximizing a yield and the yield is equal to a product of a price and a demand. In common demand functions, the demand is progressively decreased along with the increase of the price; and in chain hotel yield management, a hotel manager frequently adjusts the price upward in a great room demand, so that a feature that the demand is positively related to the price is displayed in a history data sequence. Aiming atthe feature, the invention discloses a novel demand curve estimation method which comprises the following steps of: establishing initial demand functions for demand curve estimation; updating the demand functions one by one according to history sample points; and updating the demand functions according to newly increased business day data. The method is capable of accurately describing function relationships, about prices, of demands and realizing decisions such as demand prediction, optimal pricing and room distribution of hotels.

The present application provides a pricing method for rights and interests denominated in points. The rights and interests are exercised by users when they use their services. The method includes: calculating the estimated value of the demand for the rights and interests based on the historical data of the number of times the business to which the rights and interests belong is used ;According to the estimated value of the supply and demand of the rights and interests, determine the supply and demand relationship factor; calculate the estimated value of the point consumption of the rights and interests according to the historical data of the amount of points obtained by the user; The base price determined by the estimated quantity demanded is adjusted to obtain the price of the entitlement. Through the technical solution of the application, the manual work is greatly reduced, and the situation of too much or too little exchange of rights and interests is basically avoided, and the performance of the business system will not be affected.

The invention discloses a railway passenger transport demand estimation method. The method comprises the following steps of: S1, collecting historical sales data and carrying out sales switch assignment; S2, taking the historical sales data as sample data; S3, establishing a required Gamma distribution model; S4, correcting sales restriction data in the historical sales data to obtain corrected demand data; S5, judging whether the corrected demand data meets an iteration termination condition or not, and if so, entering S7; otherwise, entering S6; S6, replacing the corresponding sales restriction data in the sample data with the corrected demand data to form a correction data set, taking the data in the correction data set as the sample data, and returning to S3; and S7, according to the correction data, calculating the integral of Gamma distribution by adopting a Simpson formula to obtain the demand of a train section target seat. The estimation method is reasonable, and the estimation result is relatively accurate.

The invention discloses a demand prediction method based on an incremental algorithm. The demand prediction method comprises the following steps of: extracting features and then carrying out differential processing on the features to obtain increments of the current features relative to historical features; carrying out differential processing on the demand to obtain an incremental demand of the current demand relative to a historical demand; constructing a feature matrix by means of the incremental features and the initial features; forming training data by using the feature matrix and the increment demand; training an incremental demand estimation model by adopting a machine learning method; and estimating the future increment by using the learned model so as to obtain future demand prediction. According to the demand prediction method, the influence of factors which cannot be quantitatively characterized on prediction can be reduced by predicting the demand increment, and the accuracy of demand prediction is effectively improved.

The invention discloses a power system stability and resource demand estimation system and method, and the method comprises the steps: carrying out the analysis of power parameters of a distributed power supply through a preset power prediction model, and obtaining a power load trend and a trend prediction value of the distributed power supply in a future preset time period; determining whether the trend prediction value meets the preset power demand threshold value or not through the analysis module, the power load data trend in the distributed power supply can be predicted in advance, the stability of the distributed power supply is predicted accordingly, coping measures can be taken in advance to solve the power supply stability problem, and economic losses are reduced.

The invention provides a COD (Chemical Oxygen Demand) detection method based on multi-sensor information fusion. The method comprises the following steps: performing oxidative digestion on a water sample to be detected by utilizing a COD detection device; recording the gas flow and the ozone concentration at an inlet of a reaction tube, the gas flow, the ozone concentration and the carbon dioxideconcentration at an outlet of the reaction tube as well as the temperature and the pressure in the reaction process in real time by multiple sensors; automatically judging whether the digestion is completed or not according to the change rate of the carbon dioxide concentration at the outlet, and if the digestion is completed, stopping digestion; then, calculating the dissolved oxygen demand and the dissolved carbon dioxide demand by utilizing a dissolved demand estimation model according to the related data measured by each sensor in the digestion process; and estimating the oxygen consumption demand according to physicochemical relation, and dividing the volume of the water sample to be detected so as to obtain the COD value of the water sample to be detected. The method and the device provided by the invention perfect the calculation process of COD detection and realize automatic judgment on digestion completion time of water samples with different concentrations or water samples containing different organic matters.