Computational Intelligence

Siddique, Nazmul; Adeli, Hojjat

doi:10.1002/9781118534823

Cited by 267 publications

(75 citation statements)

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“…In the past decade, a number of research works appeared to develop heuristic algorithms [46]. Among these algorithms, GA is the most popular one [2,3,15,22,32,55].…”

Section: Algorithms For Process Planning and Schedulingmentioning

confidence: 99%

A hybrid optimization approach for sustainable process planning and scheduling

Cai

et al. 2015

ICA

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Abstract. Process planning and scheduling are important stages in manufacturing, and good strategies can significantly improve the energy performance of manufacturing to achieve sustainability. In this paper, an innovative optimization approach has been developed to facilitate sustainable process planning and scheduling. In the approach, honey-bee mating and annealing processes are simulated to optimize multi-objectives including energy consumption, makespan and the balanced machine utilization. Experiments on practical cases show that the optimization results from this approach are promising in comparison with those from a genetic algorithm, a honey bee mating optimization algorithm, ant colony optimization and a simulated annealing algorithm, respectively.

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“…In the past decade, a number of research works appeared to develop heuristic algorithms [46]. Among these algorithms, GA is the most popular one [2,3,15,22,32,55].…”

Section: Algorithms For Process Planning and Schedulingmentioning

confidence: 99%

A hybrid optimization approach for sustainable process planning and scheduling

Cai

et al. 2015

ICA

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“…The pattern reconstruction is based on the crucial points and the ability to recall the stored pattern. Specifically, we opt to integrate 3-Sat isfiability and the Hopfield neural network as HNN-3SAT in order to solve the pattern satisfiability (Pattern-SAT) prob lem [24,25]. Basically, the Hopfield neural network is an ordinary model for content addressable memory (CAM).…”

Section: A Hopfield Modelmentioning

confidence: 99%

Enhanced Hopfield Network for Pattern Satisfiability Optimization

Mansor¹,

Kasihmuddin²,

Sathasivam³

2016

IJISA

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Abstract-Highly-interconnected Hopfield network with Content Addressable Memory (CAM) are shown to be extremely effective in constraint optimizat ion problem. The emergent of the Hopfield network has producing a prolific amount of research. Recently, 3 Sat isfiability (3-SAT) has becoming a tool to represent a variety combinatorial problems. Incorporated with 3-SAT, Hopfield neural network (HNN-3SAT) can be used to optimize pattern satisfiability (Pattern-SAT) prob lem. Hence, we proposed the HNN-3SAT with Hyperbolic Tangent activation function and the conventional McCulloch-Pitts function. The aim of this study is to investigate the accuracy of the pattern generated by our proposed algorithms. Microsoft Visual C++ 2013 is used as a platform for training, testing and validating our Pattern-SAT design. The detailed performance of HNN-3SAT of our proposed algorithms in doing Pattern-SAT will be discussed based on global pattern-SAT and running time. The result obtained fro m the simulat ion demonstrate the effectiveness of HNN-3SAT in doing Pattern-SAT.

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“…Membership functions group input data into sets, such as temperatures that are too cold, motor speeds that are acceptable, and distances that are too far. The fuzzy controller (see Figure 4) assigns the input data a grade between 0 and 1 based on how well it fits into each membership function [16].…”

Section: Journal Of Advanced Transportationmentioning

confidence: 99%

Intelligent Controller Design for Quad-Rotor Stabilization in Presence of Parameter Variations

Doukhi

Fayjie

Lee

2017

Journal of Advanced Transportation

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The paper presents the mathematical model of a quadrotor unmanned aerial vehicle (UAV) and the design of robust Self-Tuning PID controller based on fuzzy logic, which offers several advantages over certain types of conventional control methods, specifically in dealing with highly nonlinear systems and parameter uncertainty. The proposed controller is applied to the inner and outer loop for heading and position trajectory tracking control to handle the external disturbances caused by the variation in the payload weight during the flight period. The results of the numerical simulation using gazebo physics engine simulator and real-time experiment using AR drone 2.0 test bed demonstrate the effectiveness of this intelligent control strategy which can improve the robustness of the whole system and achieve accurate trajectory tracking control, comparing it with the conventional proportional integral derivative (PID).

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Computational Intelligence

Cited by 267 publications

References 0 publications

A hybrid optimization approach for sustainable process planning and scheduling

A hybrid optimization approach for sustainable process planning and scheduling

Enhanced Hopfield Network for Pattern Satisfiability Optimization

Intelligent Controller Design for Quad-Rotor Stabilization in Presence of Parameter Variations

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