[go: up one dir, main page]

So-In et al., 2015 - Google Patents

Hybrid fuzzy centroid with MDV-Hop BAT localization algorithms in wireless sensor networks

So-In et al., 2015

View HTML
Document ID
11963432617896994499
Author
So-In C
Katekaew W
Publication year
Publication venue
International Journal of Distributed Sensor Networks

External Links

Snippet

Many applications employing wireless sensor networks have been available in real-world scenarios. Their popularity is due to distinctive characteristics, for example, small scale, multisensing capability, and cost-effective deployment. However, there are constraints …
Continue reading at journals.sagepub.com (HTML) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386Retrieval requests
    • G06F17/30424Query processing
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W4/00Mobile application services or facilities specially adapted for wireless communication networks
    • H04W4/02Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS
    • H04W4/023Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0205Details
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W4/00Mobile application services or facilities specially adapted for wireless communication networks
    • H04W4/02Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS
    • H04W4/025Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS using location based information parameters
    • H04W4/028Mobile application Services making use of the location of users or terminals, e.g. OMA SUPL, OMA MLP or 3GPP LCS using location based information parameters using historical or predicted position information, e.g. trajectory data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01Social networking
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00Digital computers in general; Data processing equipment in general
    • G06F15/18Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines

Similar Documents

Publication Publication Date Title
Chen et al. Improved DV-Hop node localization algorithm in wireless sensor networks
Li et al. A Wi-Fi indoor localization strategy using particle swarm optimization based artificial neural networks
Zhao et al. Amorphous localization algorithm based on BP artificial neural network
Cui et al. A robust mobile robot indoor positioning system based on Wi-Fi
Bernas et al. Fully connected neural networks ensemble with signal strength clustering for indoor localization in wireless sensor networks
Javed et al. On precise path planning algorithm in wireless sensor network
Cao et al. An optimization method to improve the performance of unmanned aerial vehicle wireless sensor networks
Liu et al. A novel centroid localization for wireless sensor networks
Zhang et al. Improved normalized collinearity DV-hop algorithm for node localization in wireless sensor network
Kumar et al. An improved DV-Hop localization with minimum connected dominating set for mobile nodes in wireless sensor networks
Masoud et al. A hybrid clustering routing protocol based on machine learning and graph theory for energy conservation and hole detection in wireless sensor network
Vargas-Rosales et al. Performance evaluation of localization algorithms for WSNs
Chen et al. Lifetime optimization algorithm with mobile sink nodes for wireless sensor networks based on location information
So-In et al. Hybrid fuzzy centroid with MDV-Hop BAT localization algorithms in wireless sensor networks
Feng et al. Grid-based improved maximum likelihood estimation for dynamic localization of mobile robots
Shankar et al. Dynamicity of the scout bee phase for an artificial bee colony for optimized cluster head and network parameters for energy efficient sensor routing
Zhang et al. A hybrid localization approach in 3D wireless sensor network
Wu et al. Efficient range-free localization using elliptical distance correction in heterogeneous wireless sensor networks
Wang et al. An improved clustering cooperative spectrum sensing algorithm based on modified double-threshold energy detection and its optimization in cognitive wireless sensor networks
Wang et al. An improved distance vector-hop localization algorithm based on coordinate correction
Wang et al. Received signal strength–based localization for large space indoor environments
Chen et al. A low-cost anchor placement strategy for range-free localization problems in wireless sensor networks
Gao et al. A location predicting method for indoor mobile target localization in wireless sensor networks
Prasad et al. Model-contrastive federated learning entrenched UWB bi-direction localization through dynamic hexagonal grid construction in indoor WSN environment
Li et al. RMDS: Ranging and multidimensional scaling–based anchor-free localization in large-scale wireless sensor networks with coverage holes