Multispectral remote sensing data are obtained by using high resolution imaging sensors. Such data involves some problems. For example, the large number of classes, complex statistical distribution of these classes, a...
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Multispectral remote sensing data are obtained by using high resolution imaging sensors. Such data involves some problems. For example, the large number of classes, complex statistical distribution of these classes, and the smallness of the training data are among these. A new learning algorithm called self-organizing map, linear support vector machine decision tree (SOM-LSVMDT) with optimized class separability was developed to help solve complex remote sensing classifications problems. The method consists of a clustering part and a binary tree with linear support vector machine at all tree nodes. The proposed algorithm also generates a given number of clusters such that the classes chosen in each cluster are optimized in terms of a separability measure. The SOM -LSVMDT can also minimize problems associated with rare events. The performance of the SOM-LSVMDT algorithm was evaluated on a comparative basis with linear support vector machine decision tree (LSVMDT) algorithm, using three remote sensing data sets from the Colorado region. The SOM-LSVMDT was observed to yield better performance than the LSVMDT.
Path prediction is currently being considered for use in the context of mobile and wireless computing toward more efficient network resource management schemes. Path prediction allows the network and services to furth...
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Path prediction is currently being considered for use in the context of mobile and wireless computing toward more efficient network resource management schemes. Path prediction allows the network and services to further enhance the quality of service levels the user enjoys. Such mechanisms are mostly meaningful in infrastructures like wireless LANs. In this article we present a path prediction algorithm that exploits the machine learning algorithm of learning automata. The decision of the learning automaton is driven by the movement patterns of a single user but is also affected by the aggregated patterns demonstrated by all users. Simulations of the algorithm, performed using the Realistic Mobility Pattern Generator, show increased prediction accuracy.
This paper presents a feasible open-canal water-distribution control system based on the dynamic regulation principle and the theory of Kalman optimal controller. The existing nonlinear phenomena, as well as the trans...
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This paper presents a feasible open-canal water-distribution control system based on the dynamic regulation principle and the theory of Kalman optimal controller. The existing nonlinear phenomena, as well as the transport delay phenomenon are accounted for. The obtained controller is simulated using the full Saint-Venant partial differential equations
This volume collects and presents the fundamentals, tools, and processes of utilizing geospatial information technologies to process remotely sensed data for use in agricultural monitoring and management. The issues r...
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ISBN:
(数字)9783030663872
ISBN:
(纸本)9783030663865;9783030663896
This volume collects and presents the fundamentals, tools, and processes of utilizing geospatial information technologies to process remotely sensed data for use in agricultural monitoring and management. The issues related to handling digital agro-geoinformation, such as collecting (including field visits and remote sensing), processing, storing, archiving, preservation, retrieving, transmitting, accessing, visualization, analyzing, synthesizing, presenting, and disseminating agro-geoinformation have never before been systematically documented in one volume. The book is edited by International Conference on Agro-Geoinformatics organizers Dr. Liping Di (George Mason university), who coined the term “Agro-Geoinformatics” in 2012, and Dr. Berk Üstündağ (istanbultechnicaluniversity) and are uniquely positioned to curate and edit this foundational text.;The book is composed of eighteen chapters that can each stand alone but also build on each other to give the reader a comprehensive understanding of agro-geoinformatics and what the tools and processes that compose the field can accomplish. Topics covered include land parcel identification, image processing in agricultural observation systems, databasing and managing agricultural data, crop status monitoring, moisture and evapotranspiration assessment, flood damage monitoring, agricultural decision support systems and more.
This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* ...
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ISBN:
(数字)9783642291784
ISBN:
(纸本)9783642291777
This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART. The 54 revised full papers presented were carefully reviewed and selected from 90 submissions. EvoApplications 2012 consisted of the following 11 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parrallel and distributed systems), EvoCOMPLEX (algorithms and complex systems), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoHOT (bio-inspired heuristics for design automation), EvoIASP (evolutionary computation in image analysis and signal processing), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defense applications), EvoSTIM (nature-inspired techniques in scheduling, planning, and timetabling), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).
Agents are software processes that perceive and act in an environment, processing their perceptions to make intelligent decisions about actions to achieve their goals. Multi-agent systems have multiple agents that wor...
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ISBN:
(数字)9783642111617
ISBN:
(纸本)9783642111600
Agents are software processes that perceive and act in an environment, processing their perceptions to make intelligent decisions about actions to achieve their goals. Multi-agent systems have multiple agents that work in the same environment to achieve either joint or conflicting goals. Agent computing and technology is an exciting, emerging paradigm expected to play a key role in many society-changing practices from disaster response to manufacturing to agriculture. Agent and mul- agent researchers are focused on building working systems that bring together a broad range of technical areas from market theory to software engineering to user interfaces. Agent systems are expected to operate in real-world environments, with all the challenges complex environments present. After 11 successful PRIMA workshops/conferences (Pacific-Rim International Conference/Workshop on Multi-Agents), PRIMA became a new conference titled “International Conference on Principles of Practice in Multi-Agent Systems” in 2009. With over 100 submissions, an acceptance rate for full papers of 25% and 50% for posters, a demonstration session, an industry track, a RoboCup competition and workshops and tutorials, PRIMA has become an important venue for multi-agent research. Papers submitted are from all parts of the world, though with a higher representation of Pacific Rim countries than other major multi-agent research forums. This volume presents 34 high-quality and exciting technical papers on multimedia research and an additional 18 poster papers that give brief views on exciting research.
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