475 results about "Algorithm Selection" patented technology

A shared vehicle system includes a central facility, at least one vehicle distribution port facility and a plurality or fleet of vehicles, each having a vehicle subsystem. In general, the central station and port facility and the vehicle subsystems communicate in a manner to allow a user to enter information at a port facility. That information is then communicated to the central facility, where the information is processed to select a vehicle from the fleet to allocate to the user at the port facility. Selection of a vehicle for allocation to a user may be based on selecting an available or soon to be available vehicle according to various algorithms that take into account the vehicles state of charge. The central station also communicates with the port facility and the vehicle subsystem to notify the user of the selected vehicle, to provide secure user access to the selected vehicle, to monitor the location and operating status of vehicles in the fleet, to monitor the state of charge of electric vehicles and to provide other functions. The vehicles communicate with the central station to notify the central station of the PIN number of the individual attempting to use the vehicle, and of vehicle parameters such as state of charge and location of the vehicle.

Systems and methods for implementing per-session load balancing of packets that increase traffic sharing and reduce systematic unequal distribution of traffic are provided by virtue of one embodiment of the present invention. A method for operating a selected router is provided that uses a load balancing algorithm that is configured to de-correlate distribution of sessions among the active paths at the selected router relative to distributions of sessions of other algorithms at other routers of said network. Packets arriving at the selected router are assigned to an output path according to the load balancing algorithm. A method of routing a packet received at a router having an associated identifier is provided. The source address and a destination address of the packet are obtained. An output path is selected according to a load balancing algorithm that uses the associated identifier, the source address, and the destination address as inputs, and the packet is routed to the output interface associated with the selected output path. A look-up table that is configured using the identifier can be used in selecting the output path. A router storing an identifier assigned to the router is provided; the identifier is used in determining per-session routing of incoming packets.

A data storage subsystem having a plurality of data compression engines configured to compress data, each having a different compression algorithm. A data handling system is configured to select at least one sample of data; operate a plurality of the data compression engines to compress the selected sample(s); determine the compression ratios of the operated data compression engines with respect to the selected sample(s); and select the data compression engine having the greatest compression ratio with respect to the selected sample(s), to compress the data. Further, the data compression engines may be in tiers from low to high in accordance with expected latency to compress data and to uncompress compressed data; and a data compression engine is selected from a tier that is inverse to the present rate of access.

A computing system and method for selecting parameters for a data mining modeling algorithm. The computing system comprises a computer readable medium and computing devices electrically coupled through an interface apparatus. A data mining modeling algorithm and test data are stored on the computer readable medium. Each of the computing devices comprises a data subset from the a plurality of data subsets. The data mining modeling algorithm is distributed simultaneously using a selected technique to each of the computing devices. An associated parameter setting for each data mining modeling algorithm in each of the computing devices is adjusted simultaneously. Each associated parameter setting comprises a different parameter setting. Each data mining modeling algorithm comprising the associated parameter setting is run simultaneously to generate an associated data mining model on each of the computing devices. A data mining modeling algorithm comprising a best parameter setting is determined.

The invention discloses a Trojan horse detection method based on communication behavior clustering, and belongs to the field of information safety. The unknown Trojan horse detection method is excellent in feature extraction performance, proper in clustering algorithm and high in detection efficiency and accuracy in order to resolve the problems that the existing Trojan horse detection technology is low in feature extraction capacity, improper in clustering algorithm selection and the like. According to the technical scheme, the Trojan horse detection method comprises the steps of extracting a network flow data package, recombining a TCP conversation, extracting a Trojan horse reverse connecting feature, an entropy feature, a heart beat feature and the like, building a feature vector of the TCP conversation and carrying out real-time clustering on the feature vector based on a real-time increment clustering algorithm of LSH. According to the difference of communication behavior features of a Trojan horse conversation and normal network communication behaviors, the Trojan horse detection method marks the difference of the communication behavior features of the Trojan horse conversation and the normal network communication behaviors by combining the statistic analysis and the time series analysis technology, guarantees high detection accuracy and a zero false alarm rate, lowers the false alarm rate, and can effectively carry out real-time detection on the abnormal communication behaviors of a Trojan horse.

The invention discloses an intelligent layout method used for a rectangular part. The method comprises the steps that S1 relative parameters of the genetic algorithm are initialized; S2 relative information of the rectangular part is extracted from a rectangular part bank to be laid out; S3 relative information of raw material boards is extracted from a board tank; S4 the obtained information is coded, and primary species are generated randomly; S5 one-by-one decoding is conducted on the primary species by means of the lowest horizontal line search algorithm to obtain solution using efficiency; S6 selection, crossover and mutation operation is conducted according to the genetic algorithm until iteration is finished, and the optimal layout scheme is output. According to the intelligent layout method, the process requirement of the rectangular part can be met well, the intelligent algorithm and the heuristic algorithm are combined, one optimizing scheme can be found rapidly and efficiently, and therefore the material using rate of an enterprise is greatly improved, layout time can be obviously shortened, and layout efficiency is improved.

The invention discloses a disk fault detection method using multi-model prediction, which extracts multiple characteristics of disk SMART indexes through a sequential data processing means, and establishes a classification model to predict disk state. Step 1, data input: acquiring a data set composed of monitoring data of a plurality of disks in a period of time; step 2, SMART screening: adoptingmutation point detection mode to select SMART index; step 3, feature engineering: using SMART index as the input of the user-defined feature extraction module to extract the features of the SMART index, then extracting the corresponding parameter configuration, and transmitting the parameter configuration to the feature extraction module as a parameter, so as to extract the feature sets of the training set and the test set; step 4, data set balance: desampling the negative sample which occupies a large amount by adopting dimension reduction clustering; step 5, algorithm selection and modeling:on the basis of the step 4, training the classification model and testing whether the current disk belongs to the normal state or the fault state that needs to be replaced.

A new network topology visualization is produced from an existing network topology using grouping algorithms that are selectively applied to selectable hierarchies of the existing network topological hierarchy. The new network topology is rendered for review. Interaction may be provided through a graphical user interface (GUI). The new network topology is provided as a previewing visualization. The previewing visualization is provided in a tree-view. The previewing visualization provides a visual differentiation between portions of the network topology that are changed by the grouping algorithm and portions that are not changed. The grouping algorithms may be provided as plug-in algorithms. A further new network topology may be rendered in response to receipt of a changed network topology.

The invention discloses a frame loss compensation method and a frame loss compensation device for a transform domain. The method comprises the following steps: the frequency-domain coefficient of a current lost frame is calculated by using the frequency-domain coefficient of a previous frame or frequency-domain coefficients of multiple previous frames of the current lost frame, and frequency domain-time domain transform is performed to obtain an initial compensation signal; and waveform regulation is performed to obtain a compensation signal so as to reduce the operation complexity and achieve a better compensation effect. Or, for all or part of frequency points of the current lost frame, extrapolation is performed on phases and amplitudes of corresponding frequency points of multiple previous frames to obtain phases and amplitudes of corresponding frequency points of the current lost frame and to further obtain frequency-domain coefficients of the corresponding frequency points, and frequency domain-time domain transform is performed to obtain a compensation signal, thus greatly improving the tone frame compensation effect. The method can be selected through a judging algorithm to compensate the current lost frame to achieve a better compensation effect. A voice signal frame and a music signal frame are processed in a differentiated mode, and a good compensation effect can be achieved in a variety of scenarios. Through gain adjustment, the compensation energy is stabilized and the compensation noise is reduced.

This invention is a method and system for replacing an entry in a cache memory (replacement policy). The cache is divided into a high-priority class and a low-priority class. Upon a request for information such as data, an instruction, or an address translation, the processor searches the cache. If there is a cache miss, the processor locates the information elsewhere, typically in memory. The found information replaces an existing entry in the cache. The entry selected for replacement (eviction) is chosen from within the low-priority class using a FIFO algorithm. Upon a cache hit, the processor performs a read, write, or execute using or upon the information. If the performed instruction was a “write”, the information is placed into the high-priority class. If the high-priority class is full, an entry within the high-priority class is selected for removal based on a FIFO algorithm, and re-classified into the low-priority class.

Various embodiments of methods and systems for intelligent multimedia-based thermal power management implemented in a portable computing device (“PCD”) are disclosed. To reduce or increase power consumption in the PCD, embodiments adjust one or more visual multimedia parameters, the settings of which contribute to power consumption associated with an overall multimedia workload. The selection of visual multimedia parameters for setting adjustment is a function of the change in user experience versus the change in power consumption that will likely result from the setting adjustment. Exemplary visual multimedia parameters for which settings may be adjusted by certain embodiments include, but are not limited to, color depth, display brightness, GPU processing resolution, image dynamics algorithm selection, resolution scaling ratios and frames per second processing rates.

The invention relates to a method and a system for synchronously inserting network time. The method comprises the following steps: S1, a client generating an NTP (Network Time Protocol) timestamp query information packet and sending the NTP timestamp query information packet to an optimal time server, wherein the optimal time server is a time server selected by the client according to an optimal time server algorithm; S2, the client receiving an NTP timestamp answer information packet generated by the optimal time server according to the NTP timestamp query information packet; S3, repeating S1 and S2, and executing S4 when the repeated times is N, wherein N is more than or equal to 5 and less than or equal to 10, the repeated time interval is t, and t is more than or equal to 10s and less than or equal to 30s; S4, the client calculating a time difference data mean by adopting an information packet filter algorithm; S5, the client calibrating the client time according to the time difference data mean; and S6,the client displaying the calibrated client time. By adopting the method and the system, the calibrating precision is high, the system is small, the scheme is easy to realize, and the hardware cost is relatively low.

Algorithm selection for data communications in a parallel active messaging interface (‘PAMI’) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including specifications of a client, a context, and a task, endpoints coupled for data communications through the PAMI, including associating in the PAMI data communications algorithms and bit masks; receiving in an origin endpoint of the PAMI a collective instruction, the instruction specifying transmission of a data communications message from the origin endpoint to a target endpoint; constructing a bit mask for the received collective instruction; selecting, from among the associated algorithms and bit masks, a data communications algorithm in dependence upon the constructed bit mask; and executing the collective instruction, transmitting, according to the selected data communications algorithm from the origin endpoint to the target endpoint, the data communications message.

A patient monitoring system and method is disclosed herein. The system includes one or more patient monitors that obtain physiological data from a patient. Based upon the physiological data obtained from the patient, as well as the information available for the patient in an electronic health record, an algorithm selection device determines which one of a plurality of early warning algorithms are best suited for use in monitoring a patient. One or more early warning algorithms can be presented to a user for selection. Once the algorithm selection device or the user determines which of a plurality of early warning algorithms would be most effective, the early warning algorithm is downloaded to the patient monitor for use by the patient monitor. The patient monitor utilizes the downloaded early warning algorithm to generate alarms and alerts to indicate the health status of the patient being monitored.

New computational technologies generating systematic investment portfolios by coordinating forecasting algorithms contributed by researchers are provided. Work on challenges is efficiently facilitated by the algorithmic developer's sandbox (“ADS”). Second, the algorithm selection system performs a batch of tests that selects the best developed algorithms, updates the list of open challenges and translates those scientific forecasts into financial predictions. The algorithm controls for the probability of backtest overfitting and selection bias, thus providing for a practical solution to a major flaw in computational research involving multiple testing. Third, the incubation system verifies the reliability of those selected algorithms. Fourth, the portfolio management system uses the selected algorithms to execute investment recommendations. A dynamically optimal portfolio trajectory is determined by a quantum computing solution to combinatorial optimization representation of the capital allocation problem. Fifth, the crowdsourcing of algorithmic investments controls the workflow and interfaces between all of the hereinabove introduced components.

The pixel in a transflective color LCD panel of the present invention has an additional sub-pixel area. The pixel is divided into three or more color sub-pixels in R, G, B and at least one sub-pixel M. Each of the color sub-pixels is divided into a transmission area and a reflection area to display color image data. The sub-pixel M can be entirely reflective or partially reflective for displaying a further image data. Two or more algorithms are used to compute the further image data based on the color image data. A selector is used to select one of the algorithms for displaying the further image data. The algorithm selection can be used by a user or automatically selected according to the brightness of ambient light. The transflective LCD panel can be used in a reflective mode when the ambient light reaches a brightness level.

An indoor and outdoor seamless positioning system comprises a sensing layer L1, an algorithm layer L2, a hardware layer L3, a data layer L4 and an application layer L5, wherein the sensing layer L1 comprises a user request module L11, a scene module L12 and a state module L13 which are in parallel; the algorithm layer L2 comprises algorithm selection software, and algorithm selection is realized on the basis of information of a signaling set S1 sent by the sensing layer L1; the hardware layer L3 comprises hardware switch management software, and switching of hardware switch states of GNSS (global navigation satellite system) and WIFI (wireless fidelity) is completed according to an algorithm selection result of the algorithm layer L2; the data layer L4 comprises WIFI data analysis and positioning software, GNSS data analysis and positioning software and MEMS (micro-electromechanical system) positioning software; and the application layer L5 comprises client software and is used for providing position-based service for a user. The indoor and outdoor seamless positioning system has the characteristics that the system can perform self-adaptive switching of software and hardware according to scenes, so that only one of GNSS equipment and WIFI equipment is in the operating state most of the time, and terminal power is saved.

The invention discloses a multi-channel multi-path routing protocol for vehicle team ad-hoc networks. The multi-channel multi-path routing protocol mainly comprises: (1) each vehicle node is made to work on a service channel, the vehicle nodes using the same service channel form a channel transmission path in a vehicle team, and multiple transmission paths of multiple channels are formed in the vehicle team; (2) each vehicle node acquires position, speed and motion direction information of other vehicle nodes through an adaptive distributed position service; and (3) a multi-channel greedy forwarding algorithm is adopted: when the vehicle nodes send or forward a data message, a next-hop neighbor node is selected by use of the greedy forwarding algorithm according to the position of a destination node and the working channel utilization rate of a neighbor node until the data message reaches the destination node. By adopting the provided multi-channel multi-path routing protocol for vehicle team ad-hoc networks, vehicle team communication is enabled to be fully self-organized without relying on any infrastructure, adjacent vehicle nodes are allowed to communicate on different channel transmission paths at the same moment, the network throughput is improved, and the routing protocol supports multi-hop big data transmission and has practical application prospects.

Methods are described for near optimal Antenna and/or sensor selection via population-based probabilistic evolutionary algorithms such as estimation of distribution algorithm (EDA) and bio-inspired Optimization (BIO). The aspects of the invention includes a method for joint transmit and receive antenna selection using EDA; and an enhanced EDA, which uses cyclic shift register and biased estimation of distribution; and methods for joint transmit and receive antenna selection using improved population-based optimization. The proposed EDA-based and bio-inspired selection methods results in performances that are close to the ESA (exhaustive search algorithm) and yet impose mush less computational burden than ESA. Another advantage of our methods is that they can be easily implemented on parallel processors.

A branch prediction apparatus may include a first branch predictor for executing a first branch prediction algorithm and a second branch predictor for executing a second branch prediction algorithm. A choice predictor may generate a control signal for controlling operations of the first branch predictor and the second branch predictor. The choice predictor may also select and output a prediction result of the first branch predictor or the second branch predictor. The first branch predictor and the second branch predictor may respectively execute the prediction algorithms depending on the control signal. The choice predictor may include a shift register for shifting stored branch prediction values of the branch prediction apparatus to the left by one bit. A choice prediction table may be indexed by a value of the shift register to output a predictor selection value. A predictor selecting unit may generate the control signal and a selection signal for selecting an output of one of the first and the second branch predictors. An MUX circuit may output a branch prediction value of the first branch predictor or a branch prediction value of the second branch predictor depending on the selection signal. A computer-readable medium may include instructions causing a computer to perform the functions of selecting one branch predictor from among a plurality of branch predictors by using previous branch prediction results, and executing a branch prediction for a branch instruction by using the selected branch predictor.