42 results about "Preference relation" patented technology

The invention discloses an unexpected event emergency capacity assessing method based on interval binary semantics. The unexpected event emergency capacity assessing method comprises the following steps: firstly, building an emergency capacity assessing index system, and building an interval binary semantics preference relationship relevant to an assessing index through pairwise comparison; then,inspecting and correcting the consistency of the interval binary semantics preference relationship by an iterating algorithm; exporting assessing index weights and calculating a sub-index global weight; taking subjective and objective weights of a decision maker into consideration, and calculating a group sub-index global weight by using an interval binary semantics aggregation operator; acquiringan interval binary semantics assessing value of a scheme to be assessed on a sub-index; taking the subjective and objective weights of the decision maker into consideration, and calculating a group scheme assessing value by using the interval binary semantics aggregation operator; and integrating interval binary semantics interval set aggregation operators to obtain comprehensive assessing valuesof schemes for comparison and ranking. Through adoption of the unexpected event emergency capacity assessing method, information loss can be avoided, and the complexity, uncertainty and thought fuzziness of the decision maker during emergency capacity assessing can be well processed.

The invention discloses a fault diagnosis method based on sensor complementarity analysis. The fault diagnosis method comprises the following steps of: the step 1, obtaining a preference relation matrix; the step 2, acquiring a sensor complementarity vector; and the step 3, fusing the multi-sensor detection data to obtain the fault type. The method is clear in logic and reasonable in design, the sensor complementarity is analyzed according to the fault diagnosis historical data, and the multi-sensor fault diagnosis model is constructed on the basis of the sensor complementarity. Therefore, during fault diagnosis, the advantages of various sensors are comprehensively considered, the accuracy of fault diagnosis during multi-sensor detection is improved, and the fault diagnosis of the motor rotor system is helped.

Disclosed are an uplink resource allocation method and a cognitive small cell network system performing the method. In the method, a small cell manager collects an access request from a small cell user and forms a preference relationship for each small cell user. Then, sub-channel-specific transmission power for providing a maximum data transmission rate at the time of uplink transmission is calculated and the calculated sub-channel-specific transmission power information is transferred to the small cell user. Meanwhile, the small cell user forms all possible sub-channel-specific preference relations and thereafter, transmits the access request for each sub-channel having a maximum preference relationship to the small cell manager. Thereafter, the small cell user performs power allocation for each access-determined sub-channel by using the transmission power information transferred from the small cell manager and performs data transmission through the access-determined sub-channel by using the allocated power.

The invention discloses a comprehensive evaluation method of high-speed press structure schemes. A comprehensive evaluation index system of the high-speed press structure schemes is established, and a target value, which each evaluation index needs to approach or avoid, and a weight thereof are given; the evaluation index value of each candidate scheme is represented as a real number, an interval number or a triangular fuzzy number; weighted standardization is carried on deviant-type and fixed-type evaluation indexes in each candidate scheme after equivalent transformation, and weighted standardization is directly carried out on benefit and cost-type evaluation indexes; positive and negative ideal solutions are determined according to the type of each evaluation index; distances from each scheme to the respective positive and negative ideal solutions are calculated; a relative closeness degree is obtained according to the distances from each scheme to the positive and negative ideal solutions; and the candidate scheme with the maximum relative closeness degree is the best scheme. The method is based on a TOPSIS method, combines with interval probability degrees and relative preference relationships to comprehensively evaluate the high-speed press structure schemes, and can effectively obtain the best scheme with good comprehensive performance and structure manufacturability.

A method and apparatus for actuating a machine is provided in which a relaxed abduction problem is determined in order to explain the greatest possible part of the observations with the fewest possible assumptions. Based upon two preference orders over a subset of observations and a subset of assumptions, tuples are determined so that the theory together with the subset of assumptions explains the subset of observations. On the basis of the formal validity of the approach certain characteristics of the set of results (such as correctness, completeness, etc.) are checked. By the choice of underlying representational language and the preference relations, the complexity of the problem-solving process is influenced and thus flexibly adapted with regard to domain requirements. The invention may be used for any machines, e.g. gas turbines or steam turbines.

The invention discloses a scheduling method and system, and the method comprises the steps: collecting performance parameters provided by a plurality of working nodes, enabling the working nodes to beservers which bear a load balancing work task, enabling the plurality of servers to be arranged in a load balancing server cluster network, and obtaining the load state of the server cluster network;And according to the performance parameter set and the load. Missing scheduling preference information occurring after newly adding working nodes into a server cluster network under a plurality of performance parameters can be complemented; Through the construction of the multi-working-node scheduling preference relationship, all performance parameters of the working nodes are integrated, and a fuzzy relationship matrix is established for the scheduling preference of each parameter to each working node through the load balancing scheduling node to calculate missing information.

The invention discloses a parallel method for skyline query on the basis of an uncertain preference relation. The parallel method comprises the following steps: inputting a data set D; initializing a label length |L| of the data set D; generating 2L different labels according to the label length |L|; according to every selected current data tuple O traversed from the data set D; carrying out parallel calculation on values of 2L disjoint crystal lattices on skyline query Sky (O) including 2n items of the current data tuple O by using 2L processes, wherein every process calculates a crystal lattice; and adding results obtained by calculating the processes to obtain the skyline query Sky (O) of the current data tuple O and outputting the skyline query Sky (O). The parallel method for skyline query on the basis of the uncertain preference relation has the advantages that the number of the parallel processes is controllable, the parallel efficiency can be maximized, required time is reduced along with label length indexes, the query time can be greatly shortened, and efficient query can be realized.

An embodiment of the present invention provides an information recommendation method and device. The method includes: acquiring user information of a user to be recommended and item information of multiple items to be recommended; determining preference relationship information according to the reference information corresponding to the item to be recommended; Information, item information and preference relationship information are input into the information processing model to obtain the user vector, target item vector, preference relationship vector and preference relationship hyperplane; determine the sum of the projection vector of the user vector on the preference relationship hyperplane and the preference relationship vector, As the expected vector of the user to be recommended; according to the distance between the expected vector of the user to be recommended and the projected vector of the item, determine the first interest value of the user to be recommended for each item to be recommended; according to the first interest value of the item to be recommended, from the item to be recommended The target recommendation item is determined in , and the item information of the target recommendation item is pushed to the user to be recommended. By adopting this embodiment of the method, the item information of the target recommendation item can be pushed to the new user.