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Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search by Wahab, Musa

“…Hence, an electricity demand forecasting model that reflects the characteristics of electricity demand has been developed in this research. …”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

“…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm by Alam, Md. Shah, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah, Konneh, Mohamed

“…Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting little deviations in surface roughness prediction. …”
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Biodiesel synthesis from Ceiba pentandra oil by microwave irradiation-assisted transesterification: ELM modeling and optimization by Silitonga A.S., Shamsuddin A.H., Mahlia T.M.I., Milano J., Kusumo F., Siswantoro J., Dharma S., Sebayang A.H., Masjuki H.H., Ong H.C.

Correlated survivability analysis model for manets by Ab Halim, Azni Haslizan

“…However, correlated node behavior is not reflected as one of the metric in analyzing network survivability with current survivability models. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Predicting wheat yield from 2001 to 2020 in Hebei Province at county and pixel levels based on synthesized time series images of Landsat and MODIS by Zhang, Guanjin, Roslan, Siti Nur Aliaa, Mohd Shafri, Helmi Zulhaidi, Zhao, Yanxi, Wang, Ci, Quan, Ling

“…The model combining LSTM algorithm and NIRv had the best prediction effect and relatively stable performance in single year. …”
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Seismic wave modeling and high-resolution imaging by Bashir, Y., Ghosh, D.P., Alashloo, S.Y.M.

“…The wave-modeling and imaging algorithm is implemented on two velocity models: the Marmousi model and the Sigsbee model. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

“…Finally, the algorithm superiority is justified via comparing with existing solvers on benchmark problems, and the model effectiveness is exemplified by using three case studies on portfolio selection. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

“…Finally, the algorithm superiority is justified via comparing with existing solvers on benchmark problems, and the model effectiveness is exemplified by using three case studies on portfolio selection. …”
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How social media crisis response and social interaction is helping people recover from Covid-19: an empirical investigation by Bukar, Umar Ali, A. Jabar, Marzanah, Sidi, Fatimah, Nor, R. N. H., Abdullah, Salfarina, Ishak, Iskandar

“…The assessments of the reflective measurement models based on path analysis in PLS-SEM are reliable and valid. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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Rapid and non-destructive monitoring of the drying process of glutinous rice using visible-near infrared hyperspectral imaging by Jimoh, Kabiru Ayobami, Hashim, Norhashila, Shamsudin, Rosnah, Che Man, Hasfalina, Jahari, Mahirah

“…The best performance accuracy (RP2≥99.99░%)was obtained when the SG1D and Gaussian process regression (GPR) model were combined with iteratively retained informative variable algorithm (SG1D-IRIV-GPR), variable iterative space shrinkage (SG1D-VISSA-GPR) and variable combination population analysis (SG1D-VCPA-GPR) for the prediction of MC, GI, and ΔE, respectively. …”
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

“…Moreover, it results two or more nodes for each independent variable, where every node contains numbers of presence or absence of landslides (dependent variable). …”
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Effect of vibration on hydraulic conductivity of riverbank filtration site / Fauzi Baharudin by Baharudin, Fauzi

“…The results have shown that the model developed with Scaled Conjugate Gradient (SCG) algorithm provided the best prediction with values for mean squared error (MSE) of 58.59 and R of 0.86. …”
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A novel AI-driven EEG images emotion recognition generalized classification model for cross-subject analysis by Li, Jingjing, Lee, Ching Hung, Duan, Dingna, Zhou, Yanhong, Xie, Xueguang, Wan, Xianglong, Liu, Tiange, Li, Danyang, Yu, Hao, Hasan, W. Z.W., Song, Haiqing, Wen, Dong

“…AI algorithms can effectively perform encoding and decoding analysis on Electroencephalography (EEG) signals, which are widely used in emotion recognition due to their ability to reflect brain activity characteristics. …”
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Phenotyping of hypertensive heart disease and hypertrophic cardiomyopathy using personalized 3D modeling and cardiac magnetic resonance imaging / Chuah Shoon Hui by Chuah, Shoon Hui

“…Multiple CMR phenotype data consisting of geometric and dynamic variables were extracted globally and regionally from the models over a full cardiac cycle for comparison against the healthy models and clinical reports. …”
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An intelligent optical fibre Al(lll) sensor based on advanced materials-sol-gel & polyaniline-porous nanocomposite / Faiz Bukhari Mohd Suah, Abdul Mutalib Md Jani and Mohd Nasir Ta... by Mohd Suah, Faiz Bukhari, Md Jani, Abdul Mutalib, Taib, Mohd Nasir

“…An orthogonal design is utilized to design the experimental protocol, in which three variables are varied simultaneously. Feedforward-type neural networks with faster back propagation (BP) algorithm are applied to model the system, and then optimization of the experimental conditions is carried out in the neural network with 3:7:1 structure, which have been confirmed to be able to provide the maximum performance. …”
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