Search Results - (( evolution optimization approach algorithm ) OR ( control optimization sensor algorithm ))

Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing by Lim, Shun Hoe, Teo, Jason Tze Wi

“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms by Teo, Jason Tze Wi, Johnny Koh, Chin, Kim On, Chua, Bih Lii, Willey Liew, Noor Ajian Mohd. Lair, Lim, Shun Hoe

“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem by Asaad Shakir, Hameed, Mohd Aboobaider, Burhanuddin, Mutar, Modhi Lafta, Ngo, Hea Choon

“…The primary aim of this study is to propose a hybrid approach which combines Discrete Differential Evolution (DDE) algorithm and Tabu Search (TS) algorithm to enhance solutions of QAP model, to reduce the distances between the locations by finding the best distribution of N facilities to N locations, and to implement hybrid approach based on discrete differential evolution (HDDETS) on many instances of QAP from the benchmark. …”
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Adaptive Algorithm for Optimal Route Configuration in Multi-Hop Wireless Sensor Network by Shabani, Hikma, Ahmed Mohamed, Ahmed Haidar, Norhuzaimin, Julai, Musse, Mohamud Ahmed, Hoole, P.R.P., Marai, Majdi

“…This paper proposes an optimal route configuration technique based on an adaptive genetic algorithm in which the architecture of multi-hop wireless sensor network is considered as a distributed computing infrastructure. …”
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Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

“…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

“…The main focus of this paper is to find the optimal location of the collocated sensor-actuator and controller gains to actively control vibration, using a swarm intelligent algorithm called Ant Colony Optimization (ACO) and verified with Genetic Algorithm (GA). …”
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Global optimization method for continuous - Time sensor scheduling by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan C.

“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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ANT colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul affendy, Abdul Muthalif, Asan Gani, Walid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuator and controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Ant colony optimization for controller and sensor-actuator location in active vibration control by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

“…The main focus is to find the optimal location of the collocated sensor-actuatorand controller gains using a swarm intelligent algorithm called Ant Colony Optimization (ACO) which later verified with Genetic Algorithm (GA). …”
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Intelligent Energy Management in Residential Building by Zubair, Nur Faizah

“…An intelligent energy management system has been proposed in this paper to address this problem which include the integrated optimal control system consists of an occupancy sensor network and adaptive dynamic programming algorithm. …”
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Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

“…The resource allocation algorithm is developed through three phases, namely Low-Complexity Resource Allocation (LRA), Optimized Resource Allocation (ORA) and Cross-Layer Design of ORA (CLD-ORA). …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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Multiobjective design optimization of a nano-CMOS voltage-controlled oscillator using game theoretic-differential evolution by Ganesan, T., Elamvazuthi, I., Vasant, P.

“…The weighted sum scalarization approach was employed in this work in conjunction with three metaheuristic algorithms: particle swarm optimization (PSO), differential evolution (DE) and the improved DE algorithm (GTDE) (which was enhanced using ideas from evolutionary game theory). …”
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Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica... by Stonier, A.A., Chinnaraj, G., Kannan, R., Mani, G.

“…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. Design/methodology/approach: The optimal modulation index along with the switching angles are calculated for an 11 level inverter. …”
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A Novel Hybrid Harris Hawk-Arithmetic Optimization Algorithm for Industrial Wireless Mesh Networks by Devan, P.A.M., Ibrahim, R., Omar, M., Bingi, K., Abdulrab, H.

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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization by Chin, Kim On, Teo, Jason Tze Wi

“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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Crosssover-first different evolution: a comprehensive post- Hoc analysis by Jason Teo

“…Explore a new evolutionary optimization approach using Crossover-First Differential Evolution. …”
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GPU-accelerated extractive multi-document text summarization using decomposition-based multi-objective differential evolution by Wahab, Muhammad Hafizul Hazmi, Abdul Hamid, Nor Asilah Wati, Subramaniam, Shamala, Latip, Rohaya, Othman, Mohamed

“…Multi-document text summarization is computationally intensive, mainly when employing complex optimization algorithms. The computational demands increase significantly due to the integration of complex optimization algorithms and the computationally expensive repair operator. …”
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