Temporal reasoning finds many applications in numerous fields of artificial intelligence – frameworks for representing and analyzing temporal information are therefore important. Allen’s interval algebra is a calcul...
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This paper proposes an approach to the optimal fuzzy modeling of a nonlinear servo system application represented by an electromagnetic actuated clutch system. The nonlinear model of the process is first linearized ar...
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ISBN:
(纸本)9781509000593
This paper proposes an approach to the optimal fuzzy modeling of a nonlinear servo system application represented by an electromagnetic actuated clutch system. The nonlinear model of the process is first linearized around several operating points of the input-output static map of the process. Discrete-time Takagi-Sugeno (T-S) fuzzy models of the process are derived on the basis of the modal equivalence principle, and the rule consequents of these T-S fuzzy models contain the linearized state-space models of the process. Optimization problems are defined which aim the minimization of objective functions (OFs) defined as the mean of squared modeling errors (the difference between the process output and the fuzzy model output). The variables of the OFs are represented by a part of the parameters of the input membership functions. A Particle Swarm Optimization (PSO) algorithm solves the optimization problem and gives the optimal T-S fuzzy models. A set of simulation results is included to validate the PSO algorithm-based modeling approach and the optimal T-S fuzzy models for the electromagnetic actuated clutch system.
This laboratory based research build a process control system as water level scanner in interaction tank used for water cooling. The control valve parameter based on water level between tanks are interacted. The contr...
This laboratory based research build a process control system as water level scanner in interaction tank used for water cooling. The control valve parameter based on water level between tanks are interacted. The control method of tank valve ratio choosed in this reasearch is integral control and robust control. The desired control specification for maximum overshoot is 10%, peak time is 1 second, and error steady state is 0. The design process executed in physic system modelling step and system design criteria. Experiment executed using Matlab Script and Matlab Simulink. The simulation result will be compared to see an effective performance for processing of water cooling interaction tank control method. The design result for integral control can tracking reference accord to system design criteria and robust control can tracking reference without different experience either the system without disturbance or the system with disturbance.
We study the dynamic energy optimization problem in data centers. We formulate and solve the following offline problem: given a set of jobs to process, where the jobs are characterized by arrival instances, required p...
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ISBN:
(纸本)9781509014460
We study the dynamic energy optimization problem in data centers. We formulate and solve the following offline problem: given a set of jobs to process, where the jobs are characterized by arrival instances, required processing time, and completion deadlines, and given the energy requirements of switching servers ON or OFF, in which time-slot which server has to be assigned to which job, and in which time-slot which server has to be switched ON or OFF, so that the total energy is optimal for some time horizon. We formulate the offline problem as a binary integer program that can be considered as a new version of generalized assignment problem which includes new constraints stemming from deadline characteristics of jobs and the activation energy of servers. We propose an online algorithm that solves the problem heuristically, and we compare it to random assignment solution.
Occupant comfort and energy cost are the dual, explicit or implicit, objectives of advanced control strategies implemented in smart buildings. Focusing on the former, we present a novel approach for data-driven modeli...
ISBN:
(纸本)9781450342643
Occupant comfort and energy cost are the dual, explicit or implicit, objectives of advanced control strategies implemented in smart buildings. Focusing on the former, we present a novel approach for data-driven modeling of user comfort and a path for integrating the resulting models in a generic predictive framework for optimal HVAC control. This offers significant improvement potential over the static scheduling or occupancy based temperature bounds.
This paper proposes the comparison of seven nature-inspired optimization algorithms (NIOAs) applied to the tuning of proportional-integral (PI)-fuzzy controllers for a class of nonlinear direct current (DC) servo syst...
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ISBN:
(纸本)9781509020683
This paper proposes the comparison of seven nature-inspired optimization algorithms (NIOAs) applied to the tuning of proportional-integral (PI)-fuzzy controllers for a class of nonlinear direct current (DC) servo systems. The servo systems are modeled by second order dynamics with a saturation and dead zone static nonlinearity specific to the actuator. Seven NIOAs are considered, namely Simulated Annealing, Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), hybrid PSOGSA, Charged System Search (CSS), adaptive GSA and adaptive CSS, to solve optimization problem. The objective function is the weighted sum of time multiplied by squared control error plus squared output sensitivity function. The output sensitivity function is obtained from the state sensitivity models of the fuzzy control systems with respect to the modification of the process gain leading to a reduced process gain sensitivity. Three parameters of the PI-fuzzy controllers are tuned as variables of the objective function. Simulations and experimental results related to the angular position control of a laboratory nonlinear DC servo system are included.
Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system an...
Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that's hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.
The main contribution of this paper is a study of the applicability of data smashing - a recently proposed data mining method - for vehicle classification according to the "Nordic system for intelligent classific...
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ISBN:
(纸本)9781509018901
The main contribution of this paper is a study of the applicability of data smashing - a recently proposed data mining method - for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard, using measurements of road surface vibrations and magnetic field disturbances caused by passing vehicles. The main advantage of the studied classification approach is that it, in contrast to the most of traditional machine learning algorithms, does not require the extraction of features from raw signals. The proposed classification approach was evaluated on a large dataset consisting of signals from 3074 vehicles. Hence, a good estimate of the actual classification rate was obtained. The performance was compared to the previously reported results on the same problem for logistic regression. Our results show the potential trade-off between classification accuracy and classification method's development efforts could be achieved.
In Systems Biology, network-based approaches have been extensively used to effectively study complex diseases. An important challenge is the detection of network perturbations which disrupt regular biological function...
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In Systems Biology, network-based approaches have been extensively used to effectively study complex diseases. An important challenge is the detection of network perturbations which disrupt regular biological functions as a result of a disease. In this regard, we introduce a network based pathway analysis method which isolates casual interactions with significant regulatory roles within diseased-perturbed pathways. Specifically, we use gene expression data with Random Forest regression models to assess the interactivity strengths of genes within disease-perturbed networks, using KEGG pathway maps as a source of prior-knowledge pertaining to pathway topology. We deliver as output a network with imprinted perturbations corresponding to the biological phenomena arising in a disease-oriented experiment. The efficacy of our approach is demonstrated on a serous papillary ovarian cancer experiment and results highlight the functional roles of high impact interactions and key gene regulators which cause strong perturbations on pathway networks, in accordance with experimentally validated knowledge from recent literature.
Errors in data transmission cannot be known directly when the data transmission process is fulfilled, but error is often prevalent in data transmission. Faulty or missing frames or bits are standard errors and to cont...
Errors in data transmission cannot be known directly when the data transmission process is fulfilled, but error is often prevalent in data transmission. Faulty or missing frames or bits are standard errors and to control or check errors requires a unique method, in this case, the Stop-and-wait method, Go-Back-N and Selective Reject are methods that can be used to do so, comparison of time of error checking process with Stop-and-wait method, Go-Back-N and Selective Reject is very important to get the right method to check the ignorance, from testing performed that the method of Go-Back-N is much faster than the other methods.
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