Search Results - (( weight distribution modified algorithm ) OR ( parameters variation case algorithm ))

Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

“…The newly proposed logical rule and the algorithm will be the components in the logic mining model namely Weighted Systematic 2 Satisfiability Modified Reverse Analysis. …”
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Design and development of prototype robot gripper for object weight measurement by Almassri, Ahmed M. M.

“…Therefore, this study has proposed a robotic gripper prototype with a new configuration of pressure sensor distribution, based on development of grasping algorithm for object’s weight measurement. …”
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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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Backstepping Integral Super Twisting Sliding Mode Control Algorithm For Autonomous Underwater Glider by Noh, Maziyah Mat

“…The BISTSMC was tested for external disturbance and parameter variations. The BISTSMC has been benchmarked its performances with other sliding mode control (SMC) strategies to evaluate the chattering suppression of the controllers. …”
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The effect of key parameters on the design of an optimized CAES power plant by Khalaji Assadi , M, Shamshirgaran , S.R, Defaee Rad, S

“…In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is performed based on main parameters including plant loading and ambient condition and the resultant trends of each case are presented. …”
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A novel LTE scheduling algorithm for green technology in smart grid by Hindia, M.N., Reza, A.W., Noordin, K.A., Chayon, M.H.R.

“…In terms of fairness, the proposed algorithm shows 3, 7 and 9 better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively.…”
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A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network by Hindia, M.N., Reza, A.W., Noordin, K.A.

“…Moreover, the system's performance has been evaluated in terms of throughput, delay, and fairness index. The proposed algorithm is compared with existing algorithms, such as proportional fairness, modified largest weighted delay first, and exponential rule schemes. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

“…Various regression models with censored data are presented and we concentrate on four competing risks models namely, two parametric Cox’s model that is, Cox’s with Weibull distribution, Cox’s with exponential distribution and two semiparametric Cox’s model with subdistribution function that is, the weighted score function (W) and censoring complete (CC). …”
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Development of controller for an underactuated autonomous underwater vehicle (AUV) by Mat-Noh, Maziyah, Zain, Zainah Md, Abd Ghani, N. M., Abdul Wahab, Yasmin, Razali, Akhtar Razul

“…The simulation results have shown that the proposed controller provides the smallest chattering about more than 1000 times smaller than STSMC, more than 100 times smaller than back-stepping SMC in nominal, disturbance and parameter variation cases respectively. The steady error of the proposed controller also gives the smallest steady state error of four times smaller than STSMC and back-stepping SMC in all cases for pitching angle and 100 times smaller than STSMC and back-stepping for excess mass. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method by Delgoshaei, Aidin

“…It is observed that in 67% of studied cases, inflation rate can strengthen cell load variation. …”
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Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

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Robust Kernel Density Function Estimation by Dadkhah, Kourosh

“…The second method attempts to define an approach that is useable not only for unimodal distribution but also for multimodal distribution. This approach incorporates robust weights, whereby, high weights and low weights are assigned to normal (clean) and outlying observations, respectively. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

“…In terms of fairness, the proposed algorithm shows 3%, 7 % and 9% better performance compared to exponential rule, modified-largest weighted delay first and exponential/proportional fairness, respectively.…”
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Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

“…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

“…The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates.…”
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A novel chaotic flower pollination algorithm for global maximum power point tracking for photovoltaic system under partial shading conditions by Yousri D., Babu T.S., Allam D., Ramachandaramurthy V.K., Etiba M.B.

Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…When dealing with model mismatch (±15% parameter variation in critical growth and maximum glucose uptake rate) and process disturbance (±20% deviation in substrate feeding concentration), the proposed algorithm was able to handle the changes with a minor effect on the yeast yield up to 13.78% and 2.52%, respectively, across all different initial condition cases. …”
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Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian by Azri, Azfaruddin, Saian, Rizauddin

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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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