12 results about "Budget allocation" patented technology

The invention discloses a budget allocation strategy generation method and device, equipment and a storage medium, and the method comprises the steps: carrying out the disassembly of a total budget amount according to a budget period and each time period, and obtaining a budget disassembly result; performing target disassembly according to the delivery target type and the industry to which the enterprise belongs to obtain a target disassembly result; combining the budget disassembling result and the target disassembling result to obtain a preliminary budget allocation framework; embedding historical delivery data of the same industry and the optimal practice of the industry into a rule engine; and based on the preliminary budget allocation framework, the static basic data and the dynamic real-time data, generating at least two types of alternative budget allocation strategies by adopting a mode of fusing a machine learning model and an embedded rule engine. According to the method, the client side data, the platform side data and the industry side data are systematically integrated, and the distribution strategy is generated through fusion of the rule engine and the machine learning model, so that adaptive fusion and real-time optimization of the strategy are realized, and the generation efficiency is remarkably improved.

The invention relates to the field of carbon market policy design, and discloses a dynamically optimized carbon pricing strategy and budget allocation collaborative game model. Comprising a participant modeling module, a carbon pricing dynamic adjustment module, a budget allocation optimization module and a game evolution module. By establishing a cost function and a revenue function of multiple subjects such as a government and an enterprise and combining a dynamic carbon price function and a budget constraint condition, optimal resource allocation among multiple industries is realized. According to the method, a master-slave game method, a Nash equilibrium method and a reinforcement learning method are adopted, so that carbon pricing and budget allocation are co-evolved in multiple periods, and the dynamic regulation capability and excitation compatibility of the system are enhanced. Compared with the prior art, the policy execution consistency is improved, the total emission reduction cost is reduced, and the method is suitable for application scenes of regional carbon markets and multi-enterprise alliance.

The application provides a media information effect attribution and budget intelligent allocation method and system, relates to the technical field of media information, and comprises the following steps: constructing a conversion path by analyzing a user touch sequence and calculating attribution contribution weights of each media channel, and then obtaining an attribution return on investment. Based on this, a budget allocation optimization model is constructed to maximize the overall return, and a target budget scheme is generated for execution. After execution, the conduction effect of budget adjustment is analyzed through a cause-effect tracking map, and feedback is fed back to optimize the attribution weight calculation, so that dynamic closed-loop optimization and accurate effect evaluation of budget allocation are realized.

We provide the system. [Solution] Means for obtaining information on salary receipts, expenses, and savings, A means of integrating the acquired information to create a user profile, A means of analyzing spending patterns and proposing the optimal budget allocation, A means of automatically allocating the remaining amount after deducting fixed expenses and budget from the aforementioned salary to savings or investments, A means of generating and providing financial data as a report in natural language, A means of generating answers to user questions and providing educational content, A system that includes this.

The disclosure relates to a method and system for optimizing budget allocation for an application. The method includes, for a project of one or more projects associated with the application, and for an environment of one or more environments, receiving a parameter score level corresponding to a parameter, based on relevance of the parameter to the environment, wherein the parameter score level corresponds to a range of parameter score values. Further, for the project and for the environment, a mean environment budget value is derived based on the range of parameter score values corresponding to the set of parameters, and determining a project budget value based on summation of the mean environment budget value and an associated environment weightage corresponding to the one or more environments. The method further includes determining an application budget value based on summation of the project budget values.

To provide a planning AI household account book for the purpose of allocating a fund to an activity to which a user applies passion, and to provide optimum budget distribution and a fund plan in the course.SOLUTION: Means for inputting and transmitting hobbies and interests to a server; means for obtaining user data from a database; means for analyzing user data and updating prioritized information to the database; means for receiving, automatically categorizing, and updating user transaction information to the database; and means for obtaining revenue and expense information from the database; A system comprising: means for calculating and updating surplus funds to a database; means for calculating and updating budgets to a database based on user goals; means for simulating future allocation of funds; means for generating and transmitting simulation results to a server; means for generating and transmitting advice to a user based on user goals and financial conditions; and means for encrypting and storing data to a database.SELECTED DRAWING: Figure 1

The present application relates to the technical field of electronic commerce, and more particularly to a user journey attribution and budget self-optimization method for e-commerce global investment, comprising the following steps: step 1: collecting multi-channel user behavior event streams, taking the difference between the cumulative amount of conversion event condition strength values of the original sequence and the counterfactual residual sequence in the unified prediction interval as the unified window counterfactual conversion risk drop; step 2: for each target channel, obtaining the net causal attribution coefficient through multi-fold cross fitting double machine learning; step 3: constructing a cumulative attribution revenue concave utility function for each channel, forming an iterative closed loop of attribution modeling, causal debiasing and budget allocation. The present application can finely capture the timing incentive effect and decay characteristics of cross-channel touchpoints, effectively eliminate the confounding interference of user self-selection bias on attribution estimation, and ensure that the long-term cumulative revenue of the budget allocation strategy gradually approaches the theoretical optimal level in a non-stationary investment environment.

The invention provides a budget allocation method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining historical bubbling data within a preset time period; the original feature vectors of the historical bubbling data are clustered, a plurality of clusters are obtained, and each cluster corresponds to an implicit scene; based on the historical bubbling data, learning a price elasticity curve of each implicit scene; and based on the learned price elasticity curve of each implicit scene, determining an optimal budget allocation strategy of each implicit scene under the total subsidy budget limit. According to the method and the device, the implicit scene division is obtained based on the representation clustering of the implicit low-dimensional space for the obtained original feature vector of the historical bubble data, and the price elasticity curve of each implicit scene is learned, so that the optimal budget allocation strategy of different implicit scenes is formulated, the labor cost is effectively saved, and the subsidy resource utilization rate is improved.

The invention discloses a budget splitting strategy determination method and device, electronic equipment and a program product, and relates to the technical field of artificial intelligence, and the determination method comprises the steps: extracting a business data set from a database, converting business data into a budget limit value based on a preset rule, and adding the budget limit value into a corresponding budget pool, under the condition that it is detected that a user submits a budget splitting strategy on a front-end page, calling a target model based on a preset interface, analyzing the budget splitting strategy, outputting a classification result of the budget splitting strategy and budget allocation data, and under the condition that the category to which the budget splitting strategy belongs is an abnormal category, performing budget allocation on the budget splitting strategy. And judging whether the detection score of the abnormal category is greater than a preset threshold, and when the detection score of the abnormal category is greater than the preset threshold, adjusting the budget splitting strategy based on the budget allocation data to obtain a target budget splitting strategy. The technical problem that the budget splitting strategy cannot be accurately determined in the prior art is solved.

This invention relates to the field of programmatic advertising technology. More specifically, it relates to a budget allocation and pacing control method based on campaign value feedback. The method first divides the advertising campaign period into multiple time intervals according to a preset timeframe; it obtains the initial target spending for each time interval and confirms the actual spending and campaign result value of the ads already placed within each time interval, constructing a campaign time-series dataset; it calculates the unit budget value efficiency based on the campaign time-series dataset, constructs a relative score for each time interval, and constructs a target spending curve based on the relative score; it obtains the actual cumulative spending for each time interval to calculate the cumulative spending deviation, and determines the update direction of the campaign adjustment factor based on the sign direction of the cumulative spending deviation; based on the collected and calculated change in the ratio between actual spending and target spending and the change in the campaign adjustment factor, it calculates effectiveness evaluation data.

This invention relates to the field of advertising technology, specifically to a method for intelligent advertising placement and budget allocation in cross-border e-commerce based on reinforcement learning. The invention defines different agents based on different product categories and target markets. The decision-making process of each agent is constructed using an MDP model. Each agent independently deploys an Actor network, while a central server deploys a global Critic network. Each agent is trained locally, and the Critic parameters of each agent after local training are uploaded to the central server. The central server trains the global Critic network to maximize the multi-objective global reward function and then distributes the trained global Critic network to each agent, obtaining optimized Actor parameters for each agent and outputting the advertising action strategy. This invention achieves reasonable advertising placement by considering global rewards, product characteristics, and target market conditions.

We provide the system. [Solution] A method for obtaining real-time information on the usage status of meeting facilities, searching for available meeting facilities, and suggesting them to users, A means for analyzing legal or human resources documents using natural language processing to identify important sections and generate revision suggestions, A method for collecting financial data, analyzing past spending patterns, and proposing the optimal budget allocation, A means to secure real-time information on the reservation status of public resources from citizens and suggest the optimal usage time, A means of generating feedback to notify citizens of important changes and risks in administrative documents, A system that includes this.