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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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Algorithm development for optimization of a refrigeration system by Izzat, Mohamad Adnan

“…This thesis deals with algorithm development for optimization of a refrigeration system. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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Efficient transmission based on genetic evolutionary algorithm by Jin Fan, Kit Guan Lim, Helen Sin Ee Chuo, Min Keng Tan, Ali Farzamnia, Kenneth Tze Kin Teo

“…Through the simulation of the transmission performance of genetic optimization algorithm, the comparison of transmission energy consumption between GA and evolutionary algorithm is analyzed, and the evolutionary algorithm with higher transmission performance is obtained. …”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir

“…In this paper, a new variant of Manta Ray Foraging Optimization (MRFO) algorithm is introduced to deal with real parameter constrained optimization problem. …”
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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

“…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

“…The transformation results in an equivalent mixed discrete optimization problem. The transformed problemis then decomposed into a bi-level optimization problem, which is solved using a combination of an efficient discrete filled function method identified earlier and a computational optimal control technique based on the concept of control parameterization. …”
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Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm by Pham Q.B., Afan H.A., Mohammadi B., Ahmed A.N., Linh N.T.T., Vo N.D., Moazenzadeh R., Yu P.-S., El-Shafie A.

Scheduling scientific workflow using multiobjective algorithm with fuzzy resource utilization in multi-cloud environment by Farid, Mazen, Latip, Rohaya, Hussin, Masnida, Abdul Hamid, Nor Asilah Wati

“…In this respect, this paper proposes a new multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS) for scheduling scientific workflow based on particle swarm optimization (PSO) method. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

“…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty by Ali, Hazem Ibrahim, Mohd Noor, Samsul Bahari, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce

“…This paper presents a new method for tuning the weighing functions to design an H∞ controller. Based on a particle swarm optimization (PSO) algorithm the, weighting functions are tuned. …”
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Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Enhanced Image View Synthesis Using Multistage Hybrid Median Filter For Stereo Images by Ali Hussein Aboali, Maged Yahya

“…Disparity depth map estimation of stereo matching algorithm is one of the most active research topics in computer vision.In the field of image processing,many existing stereo matching algorithms to obtain disparity depth map are developed and designed with low accuracy.To improve the accuracy of disparity depth map is quite challenging and difficult especially with uncontrolled dynamic environment.The accuracy is affected by many unwanted aspects including random noises,horizontal streaks,low texture,depth map non-edge preserving, occlusion,and depth discontinuities.Thus,this research proposed a new robust method of hybrid stereo matching algorithm with significant accuracy of computation.The thesis will present in detail the development,design, and analysis of performance on Multistage Hybrid Median Filter (MHMF).There are two main parts involved in our developed method which combined in two main stages.Stage 1 consists of the Sum of Absolute Differences (SAD) from Basic Block Matching (BBM) algorithm and the part of Scanline Optimization (SO) from Dynamic Programming (DP) algorithm.While,Stage 2 is the main core of our MHMF as a post-processing step which included segmentation,merging, and hybrid median filtering.The significant feature of the post-processing step is on its ability to handle efficiently the unwanted aspects obtained from the raw disparity depth map on the step of optimization.In order to remove and overcome the challenges unwanted aspects, the proposed MHMF has three stages of filtering process along with the developed approaches in Stage 2 of MHMF algorithm.There are two categories of evaluation performed on the obtained disparity depth map: subjective evaluation and objective evaluation.The objective evaluation involves the evaluation on Middlebury Stereo Vision system and evaluation using traditional methods such as Mean Square Errors (MSE),Peak to Signal Noise Ratio (PSNR) and Structural Similarity Index Metric (SSIM).Based on the results of the standard benchmarking datasets from Middlebury,the proposed algorithm is able to reduce errors of non-occluded and all errors respectively.While,the subjective evaluation is done for datasets captured from MV BLUE FOX camera using human's eyes perception.Based on the results,the proposed MHMF is able to obtain accurate results, specifically 69% and 71% of non-occluded and all errors for disparity depth map, and it outperformed some of the existing methods in the literature such as BBM and DP algorithms.…”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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