375 results about "Self-optimization" patented technology

An embodiment of the invention relates to a method of modifying communication parameters of a wireless network, the wireless network having at least two antennas, and each of the antennas providing coverage to at least one sector. The method including obtaining measurement data for at least two sectors of the wireless network, determining, from the obtained measurement data, if a signal strength indicator of one or more sectors of the at least two sectors is at or below a target value, determining, if the one or more sectors is at or below the target value, a communication parameter to be applied to the wireless network such that the signal strength indicator of the one or more sectors is above the target value, and modifying the communication parameters of the wireless network such that the determined communication parameter is applied to the wireless network.

The invention is a Machine Learning system, method and computer program for automated transmission of Buy / Sell orders generated according to self-optimized trading parameters. Optimization could be performed according to every optimization method used. Perpetual real-time optimization (or self-optimization) of trading parameters adds Machine Learning feature to the invention. The invention provides a centralized trading system for the individual user or organization that wants to perform his trading automatically and completely without human intervention from receiving the data from the central server provider to real-time order execution in computerized financial markets. The disclosed system is integrated into a network of brokers, banks and other institutions trading on computerized markets. The system receives real-time market quotes information from a data provider remote server and uses it as an input for the defined trading strategies. These trading strategies generate Buy / Sell signals for a plurality of chosen market securities. The trading could be performed with previously optimized parameters or, alternatively, the optimization could be performed in real-time with trading strategy and its parameters being perpetually and automatically updated, and consequently the trading being performed with self-optimized parameters. The system further includes a module for storing specific order settings and risk / return information. Once execution criteria are satisfied, the order is sent for execution automatically. The system also includes a module for storing information relating to the Buy / Sell transactions and to the profit / loss accounting.

The invention relates to a coverage self-optimization method of a cellular mobile communication system, and is used for solving the problems of poor coverage, polluted pilot frequency and cross-area coverage. The method comprises the following steps of: measuring and reporting respective reference signal received power (RSRP) and respective signal-to-interference plus noise ratio (SINR) parameter values to a base station by each user; collecting the measurement parameter values reported by all users in a cell by the base station; judging whether the current network is in accordance with any one trigger condition of the three coverage problems; triggering a coverage self-optimization process based on dynamic adjustment on a lower dip angle of an antenna if the current network is in accordance with the condition and then adjusting the lower dip angle according to a preset scheme to solve the coverage problem; continuously adjusting an antenna azimuth angle and wave beam width or performing down-regulation on transmission power of the base station according to specific scenes and user types if the coverage requirement cannot be met within the adjustable ranges of the lower dip angle; and entering a coverage and capacity self-optimization process if the coverage problem cannot be solved by the measures. According to the method, each cell periodically initiates coverage liberalization operation for many times according to the steps so as to save manpower and material resources required by manual optimization and reduce the maintenance cost and the expenditure.

Fuzzy logic is utilized to control an RF amplifier and associated tuner for continuous self-optimization and automatic load matching to at least double the battery life of a battery-powered transmitter.

A network management device and method for coordination of self-optimization functions in a wireless network. A network management device for coordination of self-optimization functions includes one or more processors and an interface. The interface communicates with a plurality of enhanced node Bs (eNodeBs). The interface is arranged to receive a request to change a coverage or a capacity of an enhanced node B (eNodeB). The interface is further arranged to transmit a query to the eNodeB to obtain a self-optimizing network (SON) coordination state of the eNodeB. The one or more processors are arranged to determine whether to grant or deny the request based on a coordination policy and the SON coordination state.

An apparatus, a system, and a method to self-optimize a forbidden neighbor cell list (FNCL). A FNCL includes a list of cells sent to a user equipment (UE). The UE would not report those cells in the list to a network but may be considered by the UE for measurement purposes only. The self-optimization of the FNCL includes building a list of neighbor cells in an autonomous and / or automatic manner, with or without human intervention.

In one embodiment, a distributed intelligence agent (DIA) collects local state information from a plurality of minimalistic connected objects (MCOs) in a computer network, the local state information for each MCO comprising a corresponding neighbor list and a selected next-hop for the respective MCO, where one or more of the MCOs are configured to select their next-hop without any self-optimization. The DIA may then analyze a current routing topology, which is the combined result of the selected next-hops, in comparison to a computed optimal routing topology, and (optionally) in light of required service level agreement (SLA), to determine whether to optimize the current routing topology. In response to determining that the current routing topology should be optimized, the DIA may transmit a unicast routing instruction to one or more individual MCOs to instruct those individual MCOs how to optimize the current routing topology, accordingly.

Systems and methods for providing a framework for supporting a self organizing / optimization network (SON) feature in an over the air communications system. An enhanced mobile communications device is provided that performs functions to creating a framework for enhancing SON algorithms. The communications device stores event analysis data in an on board memory and, on certain conditions, signals the analysis to the network. The analysis includes information useful in performing SON algorithms at the network level, such as cell coverage and neighboring cell signal level information, cell selection and reselection information at different locations, relative signal strength between cell base stations at different locations, and coverage hole information. Utilizing the stored information, the network can automatically perform SON algorithms to improve network efficiency without the need for manual intervention by an operator. Embodiments include event filtering by the communications device to efficiently utilize the on board storage.

The invention relates to a coverage and capacity self-optimization device of a self-organization network in LTE / LTE-A and a method thereof. A fault detection unit monitors faults related to the coverage and the capacity in real time in a mobile communication network, a learning and matching unit learns and matches with history event knowledge, and wireless parameters are initially configured according to the most similar event. Then a parameter decision unit adjusts the initially configured wireless parameters on the premise of taking account of the mutual influence of different wireless configuration parameters, and a utility function is introduced to evaluate the efficiency of the self-optimization process to finally finish the utility maximization on the premise of comprehensively taking account of network / business and the requirements of operators, and realize the coverage and capacity automatic optimization of the self-organization network in the LTE / LTE-A. The invention has the advantages that the invention realizes the accurate position of fault sources and the correct decision by using the existing coverage and capacity self-optimization model, thereby achieving the target of coverage and capacity self-optimization.

The invention provides an organic calculation based coordination control method for a traffic signal of a zone boundary and relates to the field of urban traffic signal control and manual intelligence. A device comprises a traffic flow monitoring module, a self-optimizing module, a self-organizing module, an evolution learning module, a self-assessment module and a self-setting module. According to the method provided by the invention, the coordination among intersections of the zone boundary is realized and the traffic jam at the intersections of the zone boundary is avoided.

A method for computer-generating interaction-specific knowledge base for rapidly improving or optimizing a performance of an object comprises performing, according to computer-designed test matrices, at least several automatic experimental cycles on selected control variables. In at least one of the automatic experimental cycles after the first the computer plans a new test matrix designed to minimize or remove at least one expected two-variable interaction from a main effect of a designated control variable. A machine operating according to the method is also available.

A networked computing system, including multiple radio access nodes (RANs), multiple radio communications controllers (RCCs), and a data communications network facilitating communications amongst the RANs and the RCCs of the system. A regional RAN receives a default eMIB associated with a first type of RAN (e.g., a macrocell, microcell, picocells, or femtocell RAN types) from a RCC, in response to a registration event of a RAN initialization process. The regional RAN maintains a dynamic eMIB comprising network operating parameters determined by various self-optimization processes. The network operating parameters of the dynamic eMIB are selected to fall within a range designated by the default eMIB. During a network failure condition, the regional RAN is configured to use a temporary eMIB comprising failure level operating parameters in order to mitigate network deficiencies caused by the network failure condition.

The embodiment of the invention discloses a method for coverage self-optimization in a long-term evolution (LTE) system, which comprises the following steps of: detecting that a network coverage problem occurs in a district in the LTE system; determining a parameter adjustment strategy corresponding to the type of the detected network coverage problem according to the corresponding relation or the coverage self-optimization algorithm of the type of the pre-saved network coverage problem and the parameter adjustment strategy for solving the network coverage problem; and adjusting the related parameters of the district according to the determined parameter adjustment strategy. The embodiment of the invention discloses a system and equipment for the coverage self-optimization. By adopting the invention, the self-optimization of network coverage can be realized, thereby the network communication quality is effectively improved.

A system and associated method provides for a wireless local area network (WLAN) that permits mobile units to communicate with an external, wired network Nodes in the WLAN include multiple components, such as a base module, antenna module, and one or more wireless modules. Indeed, this system can employ two or more wireless modules that employ different short-range wireless protocols, such as IEEE 802.11-type and Bluetooth protocols. The nodes may perform self-discovery to determine modules within the node and associated functionality, as well as identify neighboring nodes to thereby establish a mesh-type network. Nodes can be configured to provide connectivity to the wired network, while others (access points) communicate wirelessly with mobile devices. The nodes may then be interconnected wirelessly, or via wires.

The invention discloses a central air-conditioning self-optimization intelligent fuzzy control device and a control method thereof. Technological parameters and indoor and outdoor environmental parameters of all control points of a central air-conditioning system are collected, running efficiency of a circulating system and control ends are tracked in real time according to actual load capacity of the system and end cold and hot source requirements, operation cycle of a main machine is optimized and adjusted, operation energy efficiency of each link of the system is comprehensively controlled, so that the system can always run under working conditions of high energy efficiency ratio. Meanwhile, process data, energy consumption data and equipment running data of the central air-conditioning system are summarized to form an intelligent control base, technical process such as analysis and operation is performed through the a central air-conditioning self-optimization intelligent fuzzy controller, new control strategies are generated, on-line upgrading control algorithm and energy-saving potential mining are achieved, energy consumption of the system is optimized, the operation is simplified, so that the operating efficiency of each device of the system is adjusted, and the aims of high efficiency, energy saving and intelligent control are achieved.

An automated electrospray ionization (ESI) device and related methods to optimize electrospray interface conditions for mass spectrometric analysis. The optimization process can be performed with calibration or optimization solutions that produce expected ESI parameters such as an ESI signal or an ion current. The ESI device may include an input / output (I / O) controller that is coupled to an electrospray assembly including an XYZ stage for positioning an electrospray emitter relative to a mass spectrometer orifice. The I / O controller may be connected to a power supply for applying an adjustable electrospray ionization voltage, and an adjustable flow regulator that alters the flow of solution by modifying applied voltage and / or pressure. A central processing unit instructs the I / O controller to control selectively the electrospray assembly based on the resultant signals from the mass spectrometer or the ion currents within the mass spectrometer in accordance with a predetermined optimization algorithm. The resulting ESI signal or ion currents are monitored and provide feedback to the I / O controller which can automatically instruct selected system components to make adjustments as needed to attain optimal settings that produce expected ESI signals or ion currents in the mass spectrometer for selected solutions.

Optimizing a plurality cell sites or sectors in a wireless network including receiving network data regarding a plurality of cell sites or sectors; determining a critical zone in which communication is degraded; determining best neighbor cell sites or sectors among the neighbor cell sites or sectors associated with the critical cell sites or sectors; determining if the critical cell sites or sectors in the critical zone have available resources for achieving a desired improvement in communications; determining if the best neighbor cell sites or sectors have available resources for achieving the desired improvement in communications; and altering wireless network parameters of the critical cell sites or sectors, or the best neighbor cells sites or sectors for achieving the desired improvement in communications. Altering wireless network parameters of the critical cell sites or sectors, or the best neighbor cell sites or sectors is performed continuously until the desired improvement in communications in the wireless network is achieved.

A memory card that adapts its operation according to the application to which it applied or the conditions under which it is operated. This allows the card to dynamical self optimize. In a first set of embodiments, the card uses host profiling where it will learn about the host during host-card interactions and the card's controller will optimize its algorithms accordingly. In another set of embodiments, the host and card will report to one another their capabilities for a quality of service negotiation. A further set of embodiments allows the storage device to memorize access sequences issued by the host under various predefined conditions, such as host reset or a power on boot sequence. The storage device can use this information to optimize operation for the expected commands. On deviation from an expected sequence, the device would memorize the new command sequence and save it, thus operating in a self-adaptive manner.

The invention relates to an automatic control system during the combustion process of a hot air furnace of a blast furnace, belonging to the field of automatic combustion control technique of the hot air furnace of the blast furnace. Firstly, the system self-learns the historical combustion data of the furnace according to the specified conditions, and determines the best coal gas and air flux of the furnace and the best initial openness of an adjusting valve to be as the initial parameters of the next combustion period. During the normal combustion stage, a control method that fuzzy control is combined with self-optimization control is adopted, the fastest increment of the temperature at the arch is taken as the object, and the air combustion proportion coefficient is quickly optimized according to the temperature change of the combustion chamber. Simultaneously, by adopting a non-difference self-adaptive single closed ring control system combined with the methods such as fuzzy control, self-learning and pulse driving and the like, the action of the adjusting valve can be effectively controlled, and precise and quick adjustment and control of the flux are realized. According to the trend change of the temperature of the waste gas, the system adopts the fuzzy control arithmetic to control the combustion rhythm. Simultaneously, the system comprehensively summarizes the manual combustion experience and achieves the object of completely automatic control without man-watching during the whole combustion process.

The invention relates to an energy-saving control system and control method of a central air conditioning freezing station. The control system is an energy conservation system with a self-learning function, and comprises a relational database, an energy consumption self-optimization controller, a rolling optimization controller, a signal acquisition control cabinet, a cooling tower control cabinet, a cooling pump control cabinet, a refrigeration pump control cabinet, and a plurality of sensors. Through relational database modeling for each main current consuming device in the central air conditioning freezing station and rolling optimization of the relational database, energy consumption associated information of each main current consuming device is obtained, and through further energy consumption self-optimization course, an optimization parameter of the operation of devices in the freezing station is obtained, thus the integral central air conditioning freezing station operates at a high-efficient and energy-saving state.

The invention discloses a connection establishment method and a connection establishment device for a relay node and a network node. The method comprises the following steps of: sending connection establishment request information which comprises a node type and / or a connection type of the connection establishment request information to a selected network node to be connected; and receiving connection establishment response information sent by the network node to be connected. By adopting the technical scheme, the relay node can automatically establish a connection with a home base station (HBTS), establish a wireless X2 interface, and directly interact information with other network nodes, so that the time delay of the information interaction is reduced; and the network is capable of self-configuration and self-optimization, so that the performance of the network is improved.

Optimizing a plurality cell sites or sectors in a wireless network includes calculating modifications to a plurality of network parameters for optimizing wireless network performance; evaluating the modification groups to determine conflicts between modifications for a same network parameter; and eliminating the conflicts between modifications for the same network parameter within the modification groups. The modification groups are used to alter at least one network parameter of the critical cell sites or sectors, or of a best neighbor cells sites or sectors for achieving a desired improvement in communications within the wireless network. Optimization is further enhanced by determining the best previous modifications to the wireless network when performance continues to be degraded. Altering wireless network parameters of the critical cell sites or sectors, or the best neighbor cell sites or sectors is performed continuously using the stored modification groups until the desired improvement in communications in the wireless network is achieved.

The invention relates to a system an a method for self optimizing a radio communication network comprising a plurality of radio cells, the system means for monitoring the network resource consumption and quality parameters individually for each cell, and means for distributing the network traffic dynamically between neighboring radio cells in order to maintain satisfactory quality of service in each radio cell.

The invention discloses a self-organized wireless local area network and a realization method thereof. A measuring module, a measuring information reporting module and an adjusting module are arranged on a user side in the network; a receiving module, a measuring module, a measuring information reporting module and a self-organized network adjusting module are arranged at an access point (AP) end; and a data acquisition module, a data mining module, a self-configuration / self-optimization analysis module and a self-organized network feedback module are arranged at a background server end, so that automatic networking and network self-optimization functions of the wireless local area network can be realized. Each user under the coverage of the wireless local area network measures wireless transmission information and feeds the measured information back to a background server through an AP, and the background server is used for acquiring and analyzing the measured information fed back by each user, judging whether a coverage or interference problem exists and automatically finishes optimized configuration of the channel and power, so that automatic configuration of a new AP is facilitated. According to the invention, self-configuration of performance parameters of the new AP and self-optimization of a configured AP are finished intelligently and automatically without manual intervention.

Embodiments of the invention relate to a system and method for dynamically scheduling resources using policies to self-optimize resource workloads in a data center. The object of the invention is to allocate resources in the data center dynamically corresponding to a set of policies that are configured by an administrator. Operational parametrics that correlate to the cost of ownership of the data center are monitored and compared to the set of policies configured by the administrator. When the operational parametrics approach or exceed levels that correspond to the set of policies, workloads in the data center are adjusted with the goal of minimizing the cost of ownership of the data center. Such parametrics include yet are not limited to those that relate to resiliency, power balancing, power consumption, power management, error rate, maintenance, and performance.

The invention provides a cloud service performance adaptive action type selection method based on deep learning. The method comprises the following steps: monitoring physical cluster data, virtual machine data and service component data; judging whether current service performance is required to be optimized or not by combining constrained events appointed in the SLA and data monitored in real time; if the current data triggers the constrained events, deciding adaptive action types according to an adaptive method base; if the current data does not trigger the constrained events, monitoring continuously; carrying out cloud service performance self-optimization according to decided adaptive action types; feeding back for learning, updating the adaptive method base and returning for monitoring continuously. The service performance of cloud service is restricted by multiple factors in the actual running environment since the cloud environment has the characteristics of high scalability and dynamic reconfiguration, and by adopting the method provided by the invention, an optimum adaptive action is selected out from an adaptive action set according to practical situations of different scenes during service performance self-optimization of the service component.

The invention discloses an intelligent cognitive wireless network system for realizing heterogeneous network convergence. New function entities with multi-domain active cognition, high-efficiency heterogeneous network resource management, and network or terminal reconstruction are added in the network elements of the existing wireless network system, namely, a cognitive information management module, an intelligent management module and a heterogeneous network convergence management module are added on a network side; a reconstruction management unit, a united wireless resource management & self-optimization unit, a cognitive information / knowledge base and cognitive information management module are added on a terminal side; four interactive interfaces, namely interfaces among operators, interfaces between the network side and the terminal side, interfaces among respective modules and interfaces among units inside the modules are arranged. Modules or units inside the modules realize information exchange via interfaces, and realize corresponding network functions jointly, so that the cognitive capacity, autonomous capacity and adaptive capacity of the network are extended, the intellectualization of network management is promoted, the efficient utilization of heterogeneous network convergence and system frequency spectrum is realized, and overall performance of the network is promoted.

The invention discloses a self-feedback junk information filtering method. Self-feedback updating of information filter regulation is implemented by self-analysis, self-decision and self-optimization according to the filtered junk information by constructing journal analysis module with manual operation as little as possible. The invention greatly improves information filtering speed and accuracy, overcomes detects of high manpower participation in traditional filtration of massive information, heavy workload, correlation of speed and accuracy with operating height of manpower, and realizes information filtering automation.

The invention discloses an overrunning virtual synchronous generator (VSG+) method with rotary inertia and damping self-optimization-trending. The method comprises the following steps: step one, a mechanical equation and an electromagnetic equation of a virtual synchronous generator (VSG) are established; step two, the rotary inertia J and damping D in a VSG model are increased as |delta f| is increased, wherein delta f is an absolute value of a difference between a power network rated frequency and the actual frequency of the VSG; and step three, according to self-adjustment of the rotary inertia J and the damping D, closed-loop control is performed on the |delta f|, and finally, grid connection of a distributed photovoltaic power generation system is realized. According to the VSG+ method with the rotary inertia and damping self-optimization-trending, provided by the invention, the rotary inertia J and the damping D in the VSG are adaptively adjusted as the |delta f| changes, the rotary inertia J and the damping D after adjustment then perform feedback regulation on the |delta f|, and finally, zero impact during grid connection of photovoltaic inverters is realized, such that the acceptance capability of a power network for the distributed photovoltaic power generation system is improved.