Systems and methods for forward market price prediction and sale of energy storage capacity are disclosed. An example transaction-enabling system may include a fleet of machines having an aggregate energy storage capacity; and a controller, comprising: an external data circuit structured to monitor an external data source and collect data from the external data source; an expert system circuit structured to predict a forward market price for energy storage capacity based on the collected data and the aggregate energy storage capacity; and a smart contract circuit structured to automatically sell at least a subset of the aggregate energy storage capacity on a forward market for energy storage capacity in response to the predicted forward market price.

Provided are methods and apparatus for scheduling automated information delivery to a user device. In examples, provided are computer-implemented methods for scheduling automated information delivery to a user device. At least a portion of the methods can be performed by a computing device including a processor. The methods can include (i) receiving, automatically via an application programming interface executed by the processor, information describing characteristics of potential hotel guests, characteristics of a hotel, and user input describing characteristics of an advertising campaign, (ii) creating, using a machine learning algorithm, advertising campaign information including instructions configured to direct an Internet search website to automatically display advertisements for the hotel that accompany search results, and (iii) sending the instructions to a server device configured automatically cause the advertisements for the hotel to be displayed on the user device. Various other methods, systems, and computer-readable media are also disclosed.

The novel invention provides methods and systems for automated production of merchandising displays. The displays can be assembled in whole, shipped in whole and filled with customer-selected products in customer-selected amounts, filled with criteria-selected products in criteria-selected amounts or both.

Various embodiments are generally directed to techniques utilizing computers to process service billing data, generate one or more groups of customers based on one or more attributes of the data, and train a recurrent neural network (RNN) to predict future bill amounts for customers. Embodiments further include techniques to predict the future bill amounts of the customers and providing an indication of the bill amounts to the customers.

A sales and marketing assistance system using predictive analytics is provided for assisting sales by leveraging predictive analytics. The sales and marketing assistance system using predictive analytics may include a database, data warehouse, parse component, analytic component, insight component, dashboard component, mapping component, contact management component, review management component, campaign component, and messaging component. A method for assisting sales by leveraging predictive analytics using the sales and marketing assistance system using predictive analytics is also provided.

A strategic decision support system is disclosed. The system can filter content received from a remote database coupled to a network to provide a graphical user interface to enable strategic decision making to expand utilization of a product. The system can include a local client computer to generate access to content stored in the remote database, at least one filtering scheme, a set of selectable filters configured to filter the content stored in the remote database according to the at least one filtering scheme, and a remote server coupled to the local client computer via the network to analyze access restrictions to the product based on a selected filter and the at least one filtering scheme to generate a graphical user interface displayed on the local client computer.

Techniques are described for determining locations of interest based on user visits. In some situations, the techniques include obtaining information about actual locations of users at various times, and automatically analyzing the information to determine particular locations in a geographic area that are of interest, such as for frequent destinations visited by users. After determining a particular location of interest, it may be represented by generating a corresponding location model to describe the geographic subarea or other location point(s) covered by the determined location of interest, and one or more points of interest (e.g., businesses, parks, schools, landmarks, etc.) may be identified that are located at or otherwise correspond to the determined location of interest. In addition, a determined location of interest may be further used in various ways, including to identify later user visits to that location (e.g., to a point of interest identified for the location).

The method (400) of determination of an emotion or sensation perception in relation to an exposure to a flavor or fragrance ingredients comprises: a step (405) of inputting, upon a computer interface, at least two flavor or fragrance physical ingredient digital representation identifiers, the resulting input corresponding to a physical composition digital identifier representative of a physical composition of physical flavor or fragrance ingredients, a step (410) of operating, by a computing device, instructions configured to associate, to the input a physical composition digital identifier, at least one value representative of: a relative ranking among the input flavor or fragrance physical ingredient digital representation identifiers relative to at least one determined perceived emotion or sensation, a value representative of the perception, for at least one input flavor or fragrance physical ingredient digital representation identifier, for at least one determined perceived emotion or sensation, and/or a value representative of a class of flavor or fragrance ingredients in a classification of flavor or fragrance ingredients by perception of perceived emotion or sensation for at least one determined emotion or sensation perception and a step (415) of providing, upon a computer interface, for the input physical composition digital identifier, at least one value obtained during the step of operating.

An online concierge system allows users to order items from a warehouse having multiple physical locations, allowing a user to order items at any given warehouse location. To select a warehouse location for a warehouse selected by a user, the online concierge system identifies a set of items that the user has a threshold likelihood of purchasing from prior orders by the user. For each of a set of warehouse locations, the online concierge system applies a machine-learned item availability model to each item of the identified set. From the availabilities of items of the set at each warehouse location of the set, the online concierge system selects a warehouse location. The online concierge system identifies an inventory of items from the selected warehouse location to the user for inclusion in an order.

Aspects of the subject disclosure may include, for example, receiving environmental data from a plurality of environmental data sources, identifying environmental risks based on the environmental data, obtaining profile information relating to a user or entity, based on the obtaining the profile information and the identifying the environmental risks, generating a recommendation for one or more locations of possible interest, and causing the recommendation to be presented to the user or entity, thereby providing location-based environmental risk information that is customized on a per user or per entity basis. Other embodiments are disclosed.