Статті в журналах: "Activation parameters optimization"

1

Fuzeau, J., M. Vasudevan, and V. Maduraimuthu. "Optimization of Welding Process Parameters for Reduced Activation Ferritic-Martensitic (RAFM) Steel." Transactions of the Indian Institute of Metals 69, no. 8 (January 9, 2016): 1493–99. http://dx.doi.org/10.1007/s12666-015-0717-3.

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Natrayan, L., S. Kaliappan, S. Chinnasamy Subramanian, Pravin P. Patil, S. D. Sekar, Y. Sesha Rao, and Melkamu Beyene Bayu. "Optimization of Activated Carbon Fiber Preparation from Hemp Fiber through Dipotassium Hydrogen Phosphate for Application of Thermal Storage System." Adsorption Science & Technology 2023 (April 21, 2023): 1–9. http://dx.doi.org/10.1155/2023/7228408.

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With significant benefits over many other commercialised thermal storage methods, activated carbon fiber (ACF) is believed to be among the finest biosorbents for adsorbent purposes. If correctly made, it is an outstanding mesoporous lightweight material with micropores and, in most cases, no micropores. ACF’s higher bulk densities and great dynamic capacity demonstrate its value and are used in adsorbent technologies. The present study’s primary goal is to create active carbon fiber from organic hemp fiber. The following parameters were selected: (i) activating temperatures, (ii) activating timing, (iii) carbonization temperature, (iv) activating ingredient %ages, and (v) speed of activation temperature, all with four levels to achieve the goal. Taguchi optimization techniques were used to optimize the adsorbent characteristics. The current study used an L16 orthogonal array to accomplish that improvement. According to the previous Taguchi, the optimal conditions were 300°C combustions, insemination with 22.5% w / v K2HPO4 solution, and activating at 800°C for 3 hours at 20°C/min. The greatest contribution is 54.75%, followed by the rate of temperature activation at 23.35%, carbonated temperature at 10.14%, duration of stimulation at 8.82%, and H3PO4 concentrations at 2.94%. The results show that the activation temperature and rate of the temperature of activations are the essential elements in the current study’s accomplishment of the best adsorption capacities.

3

Akhmetzhanov, Talgat, Gulmira Danenova, and Andrey Rusanov. "Optimization of Low-Clinker Binder Production Technological Parameters." Key Engineering Materials 683 (February 2016): 243–49. http://dx.doi.org/10.4028/www.scientific.net/kem.683.243.

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This paper presents an experimental investigation of the mechanochemical activation the low-clinker binder production systems on the basis of CaO and Ca(OH)2. It is shown that the effects of the mechanochemical interactions of the investigated components of low-clinked binders with the superplasticizer C-3 do not show a significant effect on the binders’- properties. The main influence is observed in the interaction of Portland cement and superplasticizer C-3. This study aimed to optimize the technological parameters of low-clinker binders’ production using different by-products. The expected economic effects of low - clinked binders is associated with the reduced amount of the clinker as one of the expensive components. Taking into account the cost of using the superplasticizer C-3 and various technological wastes the economic impact is expected to be 20-25% decrease of the total cost in the concrete production.

4

Zelentsov, Dmytro, and Shaptala Taras. "Models and methods of learning neural networks with differentiated activation functions." System technologies 6, no. 143 (November 13, 2023): 57–68. http://dx.doi.org/10.34185/1562-9945-6-143-2022-05.

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Analysis of the literature made it clear that the problem associated with improving the performance and acceleration of ANN learning is quite actual, as ANNs are used every day in more and more industries. The concepts of finding more profitable activation functions have been outlined a lot, but changing their behavior as a result of learning is a fresh look at the problem. The aim of the study is to find new models of optimization tasks for the formulated prob-lem and effective methods for their implementation, which would improve the quality of ANN training, in particular by overcoming the problem of local minima. A studied of models and methods for training neural networks using an extended vector of varying parameters is conducted. The training problem is formulated as a continuous mul-tidimensional unconditional optimization problem. The extended vector of varying parameters implies that it includes some parameters of activation functions in addition to weight coeffi-cients. The introduction of additional varying parameters does not change the architecture of a neural network, but makes it impossible to use the back propagation method. A number of gradient methods have been used to solve optimization problems. Different formulations of optimization problems and methods for their solution have been investigated according to ac-curacy and efficiency criteria. The analysis of the results of numerical experiments allowed us to conclude that it is expedient to expand the vector of varying parameters in the tasks of training ANNs with con-tinuous and differentiated activation functions. Despite the increase in the dimensionality of the optimization problem, the efficiency of the new formulation is higher than the generalized one. According to the authors, this is due to the fact that a significant share of computational costs in the generalized formulation falls on attempts to leave the neighborhood of local min-ima, while increasing the dimensionality of the solution space allows this to be done with much lower costs.

5

Jiang, Li, Fei Ma, Ai Jun Gu, and Li Jun Zhang. "Production of Activated Carbon from Ligin: Optimization Using Response Surface Methodology." Advanced Materials Research 213 (February 2011): 427–31. http://dx.doi.org/10.4028/www.scientific.net/amr.213.427.

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Activated carbon（AC）were prepared from lignin by chemical activation with sodium hydroxide（NaOH）. The influence of activation temperature，activation time and impregnation ration on the BET surface areas were investigated. Based on the central composite design (CCD) and response surface methodology(RSM)，the optimized technological parameters were as follows: temperature 751°C， time 57min and impregnation ration 2.06, BET surface areas was up to 1437.20 m2/g.The adequacy of the model equation for predicting the optimum response values was verified effectively by the validation.

6

Gao, Feng, Ying Xin Ge, Jia Zhao, and Hai Xia Yang. "Technology Optimization Study on Preparation of Activated Carbon from Rice Husk Cracking." Advanced Materials Research 197-198 (February 2011): 931–34. http://dx.doi.org/10.4028/www.scientific.net/amr.197-198.931.

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Response surface methodology (RSM) was adopted to study the key parameters such as activation temperature, activation time, and active agent amount in order to increase activated carbon iodine adsorption value from rice husk. A second order quadratic equation was established and the applicability of model and interaction involved factors on predicting the iodine adsorption value was verified. The results indicated that the effect on the iodine adsorption value was as follows: activation temperature, activation ratio, activation time. The optimal levels for achieving the highest iodine adsorption value were obtained, including activation temperature of 550°C, activation time of 48min and activation ratio of 1.25. The iodine adsorption value reached 1464.793mg/g under optimized conditions. Iodine adsorption value was conducted under the optimum condition and the results showed the average relative error 0.58%, it proved that the models fitted well, the experimental data and the model were feasible.

7

Zhao, W., M. Fan, H. Gao, and H. Wang. "Central composite design approach towards optimization of super activated carbons from bamboo for hydrogen storage." RSC Advances 6, no. 52 (2016): 46977–83. http://dx.doi.org/10.1039/c6ra06326h.

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Super activated carbons were developed from moso bamboo and central composite design was used to determine optimum responses by investigating the influence of activation parameters, weight ratio of KOH/precursor (W) and activation temperature (T).

8

Chen, Liqing, Wanjun Li, Yang Yang, and Wei Miao. "Evaluation and optimization of vehicle pedal comfort based on biomechanics." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 5 (September 27, 2019): 1402–12. http://dx.doi.org/10.1177/0954407019878355.

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Existing research on the manipulation comfort of the cab pedal generally focuses on the completion of the pedal movement when a vehicle is at rest, with certain data collected for analysis. This paper, by taking passenger vehicles in China as the study object and in view of the actual road conditions in China and the Chinese body size, attempts to solve the problem of muscle redundancy through the maximum/minimum optimization model of muscle activation. The road test was carried out on a typical pavement in a Chinese city. The parameters of pedal stroke, pedal force, and typical Electromyography signal (EMG) signal of drivers’ lower limbs during driving were obtained, from which muscle activation degree was calculated. The obtained experimental data were used as external driving one to simulate and analyze the pedal comfort under the layout of different human percentile and different pedal parameters in an aim to obtain the optimal value. The results indicate that the difference in pedal strokes, pedal preload, pedal resistance coefficients, seat heights, and H-point distances can have a noticeable effect on muscle activation. Taking a 95th-percentile accelerator pedal as an example, with the optimal values of each parameter selected (pedal preload: 8.2 N, pedal resistance coefficient: 2.55, seat height: 0.45 m and H-point distance: 0.86 m), as the pedal strokes increase, muscle activation shows a trend of increase after initial decrease. In the common stroke of a pedal after optimization, the degree of muscle activation is significantly lower than that before optimization, indicating a decrease in muscle fatigue.

9

Chen, Guo, Kun Xiong, Jinhui Peng, and Jin Chen. "Optimization of combined mechanical activation-roasting parameters of titania slag using response surface methodology." Advanced Powder Technology 21, no. 3 (May 2010): 331–35. http://dx.doi.org/10.1016/j.apt.2009.12.017.

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Rožić, Ljiljana, Tatjana Novaković, and Srđan Petrović. "Modeling and optimization process parameters of acid activation of bentonite by response surface methodology." Applied Clay Science 48, no. 1-2 (March 2010): 154–58. http://dx.doi.org/10.1016/j.clay.2009.11.043.

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11

Bari, Z., S. Chasapoglou, A. Kalamara, T. Vasilopoulou, M. Axiotis, A. Lagoyannis, M. Kokkoris, R. Vlastou, and I. E. Stamatelatos. "Fast Neutron Activation Analysis at the NCSRD Tandem Accelerator facility: Prognosis and Optimization." HNPS Advances in Nuclear Physics 28 (October 17, 2022): 257–60. http://dx.doi.org/10.12681/hnps.4798.

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Neutron Activation Analysis Prognosis and Optimization (NAAPRO) code was applied for the prognosis of the activation products, their activities, the number of counts recorded in the detector, the minimum detection limits as well as the gamma spectrum obtained in fast neutron activation analysis experiments. Simulations were performed for geological and biological reference materials irradiated with 14 MeV neutrons at the 5.5 MV NCSRD tandem accelerator facility. The results of the study demonstrated the fast neutron analytical capabilities of the accelerator and, moreover, allowed for the optimization of the FNAA parameters, while avoiding the performance of difficult and time-consuming experimental tests at the accelerator facility.

12

Kandhro, Irfan Ali, Mueen Uddin, Saddam Hussain, Touseef Javed Chaudhery, Mohammad Shorfuzzaman, Hossam Meshref, Maha Albalhaq, Raed Alsaqour, and Osamah Ibrahim Khalaf. "Impact of Activation, Optimization, and Regularization Methods on the Facial Expression Model Using CNN." Computational Intelligence and Neuroscience 2022 (June 16, 2022): 1–9. http://dx.doi.org/10.1155/2022/3098604.

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When it comes to conveying sentiments and thoughts, facial expressions are quite effective. For human-computer collaboration, data-driven animation, and communication between humans and robots to be successful, the capacity to recognize emotional states in facial expressions must be developed and implemented. Recently published studies have found that deep learning is becoming increasingly popular in the field of image categorization. As a result, to resolve the problem of facial expression recognition (FER) using convolutional neural networks (CNN), increasingly substantial efforts have been made in recent years. Facial expressions may be acquired from databases like CK+ and JAFFE using this novel FER technique based on activations, optimizations, and regularization parameters. The model recognized emotions such as happiness, sadness, surprise, fear, anger, disgust, and neutrality. The performance of the model was evaluated using a variety of methodologies, including activation, optimization, and regularization, as well as other hyperparameters, as detailed in this study. In experiments, the FER technique may be used to recognize emotions with an Adam, Softmax, and Dropout Ratio of 0.1 to 0.2 when combined with other techniques. It also outperforms current FER techniques that rely on handcrafted features and only one channel, as well as has superior network performance compared to the present state-of-the-art techniques.

13

Zamora, Julio, Anthony D. Rhodes, and Lama Nachman. "Fractional Adaptive Linear Units." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (June 28, 2022): 8988–96. http://dx.doi.org/10.1609/aaai.v36i8.20882.

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This work introduces Fractional Adaptive Linear Units (FALUs), a flexible generalization of adaptive activation functions. Leveraging principles from fractional calculus, FALUs define a diverse family of activation functions (AFs) that encompass many traditional and state-of-the-art activation functions. This family includes the Sigmoid, Gaussian, ReLU, GELU, and Swish functions, as well as a large variety of smooth interpolations between these functions. Our technique requires only a small number of additional trainable parameters, and needs no further specialized optimization or initialization procedures. For this reason, FALUs present a seamless and rich automated solution to the problem of activation function optimization. Through experiments on a variety of conventional tasks and network architectures, we demonstrate the effectiveness of FALUs when compared to traditional and state-of-the-art AFs. To facilitate practical use of this work, we plan to make our code publicly available

14

Wanto, Anjar, Ni Luh Wiwik Sri Rahayu Ginantra, Surya Hendraputra, Ika Okta Kirana, and Abdi Rahim Damanik. "Optimization of Performance Traditional Back-propagation with Cyclical Rule for Forecasting Model." MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer 22, no. 1 (November 30, 2022): 51–82. http://dx.doi.org/10.30812/matrik.v22i1.1826.

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The traditional Back-propagation algorithm has several weaknesses, including long training times and significant iterations to achieve convergence. This study aims to optimize traditional Back-propagation using the cyclical rule method to cover these weaknesses. Optimization is done by changing the training function and standard Back-propagation parameters using the training function and cyclical rule parameters. After that, a comparison of the two results will be carried out. This study uses quantitative method of time-series data on coronavirus cases sourced from the Worldometer website, then analyzed using three forecasting models with five input layers, one hidden layer (5, 10, and 15 neurons) and one output layer. The results showed that the 5-10-1 model with the training function and cyclical rule parameters and the tansig and purelin activation functions could perform well in optimization, including faster training time and smaller iterations (epochs), MSE training performance, and better tests. Low and high accuracy (92%) with an error rate of 0.01. So it was concluded that the training function and cyclical rule parameters with the tansig and purelin activation functions were able to optimize the traditional Back-propagation method, and the 5-10-1 model could be used for forecasting active cases of the coronavirus in Asia

15

Kuykendal, Michelle, Stephen DeWeerth, and Martha Grover. "Optimization of Stimulation Parameters for Targeted Activation of Multiple Neurons Using Closed-Loop Search Methods." Processes 5, no. 4 (December 11, 2017): 81. http://dx.doi.org/10.3390/pr5040081.

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Cesarano, F., M. Maurizi, C. Gao, F. Berto, F. Penta, and C. Bertolin. "Preliminary optimization of shape memory polymers geometric parameters to enhance the thermal loads' activation range." Procedia Structural Integrity 42 (2022): 1282–90. http://dx.doi.org/10.1016/j.prostr.2022.12.163.

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Őze, Csilla, and Éva Makó. "Optimization of Grinding Parameters for the Mechanochemical Activation of Kaolin with the Addition of Trass." Minerals 13, no. 7 (July 7, 2023): 915. http://dx.doi.org/10.3390/min13070915.

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At present, to achieve further reductions in CO2 emissions in the cement industry, it is essential to improve the efficiency of grinding processes and reduce the energy demand. This study examined the effects of various grinding parameters (addition of trass, ball to powder mass ratio (BPR), material of grinding bodies and jars, rotational speed, and mill type) to minimize the energy consumption of the mechanochemical activation of kaolinite. X-ray diffraction, Fourier transform infrared spectroscopy, inductively coupled plasma optical emission spectroscopy, scanning electron microscopy, and specific surface area measurements were used to examine the influence of grinding parameters. It was found that the addition of as little as 25% (mass percent) trass reduced the specific energy demand for the complete amorphization of kaolinite by 56%. The application of steel grinding bodies (instead of ZrO2 ones) had a slight influence on the amorphization kinetics of kaolinite, but it could mechanochemically activate 30% more samples at the same BPR and specific energy demand. The use of the four-pot milling instead of the one-pot could considerably decrease the specific energy demand of the complete and incomplete (α = 0.9) amorphization of kaolinite. Overall, a 94% reduction was achieved in specific energy demand with steel grinding material, 14:1 BPR, four-pot milling, and the incomplete amorphization of kaolinite.

18

Mao, Decai, Yu Jia, Ping Peng, Da Shen, Xingjie Ren, Ruibao Zhu, Yuhao Qiu, et al. "Enhanced Efficiency of flySAM by Optimization of sgRNA Parameters in Drosophila." G3: Genes|Genomes|Genetics 10, no. 12 (October 5, 2020): 4483–88. http://dx.doi.org/10.1534/g3.120.401614.

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The flySAM/CRISPRa system has recently emerged as a powerful tool for gain-of-function studies in Drosophila melanogaster. This system includes Gal4/UAS-driven dCas9 activators and U6 promoter-controlled sgRNA. Having established dCas9 activators superior to other combinations, to further enhance the efficiency of the targeting activators we systematically optimized the parameters of the sgRNA. Interestingly, the most efficient sgRNAs were found to accumulate in the region from -150bp to -450bp upstream of the transcription start site (TSS), and the activation efficiency showed a strong positive correlation with the GC content of the sgRNA targeting sequence. In addition, the target region is dominant to the GC content, as sgRNAs targeting areas beyond -600bp from the TSS lose efficiency even when containing 75% GC. Surprisingly, when comparing the activities of sgRNAs targeting to either DNA strand, sgRNAs targeting to the non-template strand outperform those complementary to the template strand, both in cells and in vivo. In summary, we define criteria for sgRNA design which will greatly facilitate the application of CRISPRa in gain-of-function studies.

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Kahlmann, Willi, Emanuel Poremba, Danila Potyagaylo, Olaf Dössel, and Axel Loewe. "Modelling of patient-specific Purkinje activation based on measured ECGs." Current Directions in Biomedical Engineering 3, no. 2 (September 7, 2017): 171–74. http://dx.doi.org/10.1515/cdbme-2017-0177.

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AbstractThe Purkinje system is part of the fast-conducting ventricular excitation system. The anatomy of the Purkinje system varies from person to person and imposes a unique excitation pattern on the ventricular myocardium, which defines the morphology of the QRS complex of the ECG to a large degree. While it cannot be imaged in-vivo, it plays an important role for personalizing computer simulations of cardiac electrophysiology. Here, we present a new method to automatically model and customize the Purkinje system based on the measured electrocardiogram (ECG) of a patient. A graphbased algorithm was developed to generate Purkinje systems based on the parameters fibre density, minimal distance from the atrium, conduction velocity, and position and timing of excitation sources mimicking the bundle branches. Based on the resulting stimulation profile, the activation times of the ventricles were calculated using the fast marching approach. Predescribed action potentials and a finite element lead field matrix were employed to obtain surface ECG signals. The root mean square error (RMSE) between the simulated and measured QRS complexes of the ECGs was used as cost function to perform optimization of the Purkinje parameters. One complete evaluation from Purkinje tree generation to the simulated ECG could be computed in about 10 seconds on a standard desktop computer. The measured ECG of the patient used to build the anatomical model was matched via parallel simplex optimization with a remaining RMSE of 4.05 mV in about 16 hours. The approach presented here allows to tailor the structure of the Purkinje system through the measured ECG in a patient-specific way. The computationally efficient implementation facilitates global optimization.

20

Othman, Radzali, and Azlila Zakaria. "OPTIMISATION OF MILLING PARAMETERS DURING MECHANICAL ACTIVATION FOR DIRECT SYNTHESIS OF HYDROXYAPATITE." ASEAN Engineering Journal 1, no. 4 (January 12, 2011): 5–11. http://dx.doi.org/10.11113/aej.v1.15307.

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Mechanical activation is one of the methods to synthesize a single-phase hydroxyapatite. In this work, hydroxyapatite was directly synthesized by mechanical milling in a planetary ball mill, using calcium phosphate dibasic dihydrate, CaHPO4.2H2O, and calcium hydroxide, Ca(OH)2, as the precursors or raw materials. The milling parameters investigated included the duration of milling, the milling media, and the ball-to-powder ratio (BPR). The results thus far indicated that the parameters of milling can be optimised down to 2 hours of milling duration, using either stainless steel or agate milling media, and a BPR of 10:1. The optimization was confirmed principally by x-ray diffraction (XRD) which indicated that only single-phase hydroxyapatite was the final product in this milling reaction. Other characterization methods employed were scanning electron microscopy (SEM), transmission electron microscopy (TEM) and particle size analysis. Characterization by SEM and TEM showed that the morphologies of the hydroxyapatite particles are needle-shaped and the sizes are dependent on the changes in the parameters used in the mechanical activation milling process.

21

Kandhro, I. A., S. Z. Jumani, F. Ali, Z. U. Shaikh, M. A. Arain, and A. A. Shaikh. "Performance Analysis of Hyperparameters on a Sentiment Analysis Model." Engineering, Technology & Applied Science Research 10, no. 4 (August 16, 2020): 6016–20. http://dx.doi.org/10.48084/etasr.3549.

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This paper focuses on the performance analysis of hyperparameters of the Sentiment Analysis (SA) model of a course evaluation dataset. The performance was analyzed regarding hyperparameters such as activation, optimization, and regularization. In this paper, the activation functions used were adam, adagrad, nadam, adamax, and hard_sigmoid, the optimization functions were softmax, softplus, sigmoid, and relu, and the dropout values were 0.1, 0.2, 0.3, and 0.4. The results indicate that parameters adam and softmax with dropout value 2.0 are effective when compared to other combinations of the SA model. The experimental results reveal that the proposed model outperforms the state-of-the-art deep learning classifiers.

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Nascimento, Lucio Fabio Cassiano, Fernanda Santos da Luz, Ulisses Oliveira Costa, Fábio de Oliveira Braga, Édio Pereira Lima Júnior, and Sergio Neves Monteiro. "Curing Kinetic Parameters of Epoxy Composite Reinforced with Mallow Fibers." Materials 12, no. 23 (November 28, 2019): 3939. http://dx.doi.org/10.3390/ma12233939.

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Knowledge about the curing behavior of a thermosetting resin and its composites includes the determination of kinetic parameters and constitutes an important scientific and technological tool for industrial process optimization. In the present work, the differential scanning calorimetry (DSC) technique was used to determine several curing parameters for pure epoxy and its composite reinforced with 20 vol % mallow fibers. Analyses were performed with heating rates of 5, 7.5, and 10 °C/min, as per the ASTM E698 standard. The kinetic related parameters, that is, activation energy (E), Avrami’s pre-exponential factor (Z), and mean time to reach 50% cure (t½), were obtained for the materials, at temperatures ranging from 25 to 100 °C. Response surfaces based on the mathematical relationship between reaction time, transformed fraction, and temperature were provided for optimization purposes. The results showed that the average curing time used for the production of diglycidyl ether of bisphenol A/triethylenetetramine (DGEBA/TETA) epoxy systems or their composites reinforced with natural mallow fibers can be considerably reduced as the temperature is increased up to a certain limit.

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Ashtiani, Mohammed N., and Mahmood-Reza Azghani. "PREDICTIVE MODELS FOR ESTIMATION OF THE HUMAN STANCE EQUILIBRIUM PARAMETERS USING INVERSE DYNAMICS AND RESPONSE SURFACE METHOD." Journal of Musculoskeletal Research 20, no. 03 (September 2017): 1750016. http://dx.doi.org/10.1142/s0218957717500166.

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Activation of the muscles and reaction forces of the joints rely on the body posture. The aim of the present paper is to investigate the relationship between the kinematics of static postures and muscle activation and joint forces by means of predictive regression models. To cover a reasonable number of postures and muscle recruitment patterns in forward inclinations, 4096 postures were analyzed. The response surface method was used to estimate the results of optimization-based inverse dynamics analysis. Two sorts of input variables (three angular positions of the lower limb joints and optimized muscular activation levels) and two model responses (muscle activation and joint force) were designed. The predictive models showed adequate goodness-of-fit in average ([Formula: see text]). The predictive models that applied on the feasible balanced postures revealed considerable reliance of the biomechanical efforts on the postural angles. The ankle force was majorly supported by activation of the calf muscles as [Formula: see text] (kN). The knee and the hip joint were dominantly influenced by the hamstring activation. Quantitative assessment of biomechanical parameters in the balanced standing postures may help researchers in finding standing information by knowing one type of experimental data such as the kinematic angles or the muscle electromyography.

24

Tian, Jingwen, Meijuan Gao, and Guangshuang Ge. "Research on Intelligent Optimization Control Method for Oil Pumping." Advances in Mechanical Engineering 6 (January 1, 2014): 926958. http://dx.doi.org/10.1155/2014/926958.

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In the oil production process, some oil pumps exist in the light load running and empty pumping problems, which result in the waste of electric energy. In order to realize the oil pumping energy saving optimal control by adopting oil pumping start-stop intermittent control scheme, an intelligent energy saving optimal control system based on genetic algorithm and wavelet neural network is proposed in this paper. The Morlet wavelet is adopted as the activation function of neural network and builds the wavelet neural networkandthe structure and parameters of the wavelet neural network which are chromosome encoded, and the genetic algorithm is used to optimize the connection weights and the scale parameters in order to improve the generalization ability and the approximation ability of neural networks. The parameters of effective oil pumping energy saving optimal control are measured using multisensors. The system is used in the oil production plant; the test data show that the oil pumping energy conservation effect is obvious.

25

Ren, Xiaoling, Xinqian Shu, Haisheng Li, Jiushuai Deng, Peng Li, and Sixue Qin. "Optimization of Process Parameters and Kinetics Analysis of Cd Removal in ZnSO4 Production." Processes 9, no. 8 (August 19, 2021): 1437. http://dx.doi.org/10.3390/pr9081437.

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In order to optimize the process parameters of Cd removal in the ZnSO4 production process and study the mechanism of Cd removal reaction, the response surface methodology was used to arrange Cd removal experiments and analyze the optimal production conditions, and the mechanism of Cd removal was studied using kinetics. The results show that the optimal process conditions for Cd removal are as follows: reaction temperature 55 °C, reaction time 13.43 min, and the zinc powder dosage should be 2.14 times that of Cd; the main effects of the three variables from large to small are zinc powder dosage, reaction temperature and reaction time; Cd removal is a second-order reaction, and the activation energy of the reaction is 29.6986 kJ/mol, so the reaction conforms to the diffusion control mechanism.

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Lin, Hang, Ziyi Yin, and Su Li. "Optimization of Cementitious Material with Thermal-Activated Lead–Zinc Tailings Based on Response Surface Methodology." Materials 17, no. 12 (June 14, 2024): 2926. http://dx.doi.org/10.3390/ma17122926.

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The accumulation of lead–zinc tailings will cause a series of problems, including geological disasters and environmental pollution. Efficient secondary utilization of lead–zinc tailings is crucial. In this study, the activity of lead–zinc tailings was stimulated by thermal activation. The optimal thermal activation parameters are a thermal activation temperature of 900 °C and a holding time of 30 min. Based on the response surface methodology, the effect of raw materials content on cementitious material strength was analyzed, and the relational model between cementitious material strength and experimental variables was established. The results show that the sensitivity order of cementitious material strength at 28 days curing age is sand/cement ratio > water/cement ratio > fly ash content > tailing content. According to the relational model, the optimal materials ratio is as follows: tailing/fly ash/cement = 28.99%:14.58%:56.43%, and the sand/binder ratio and water/binder ratio are 1:1 and 0.47, respectively. The corresponding cost is CNY 290.965 per ton, which is the lowest. The strength of cementitious material with these parameters can reach 20 MPa, which meets the requirements of “Technical specification for application of solid waste cementitious material (T/CECS 689-2020)”.

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Storchevoy, Vladimir F. "Parameters of the operation mode of the electric activator for disinfection and growth support of vegetable plants." Agricultural Engineering, no. 2 (2023): 63–68. http://dx.doi.org/10.26897/2687-1149-2023-2-63-68.

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Activated solutions (catholyte and anolyte) are used for disinfection and growth of vegetable plants. To water vegetable plants with catholyte and disinfect them with anolyte, the authors have designed a single-phase fl ow-through electric activator consisting of two symmetrical chambers - that of a cathode and an anode type. The capacity of each chamber is 25 l/h. At the rated operating mode of the electric activator the change in the hydrogen index of water consumed is 3.5. The authors have determined design parameters, electrode spacing, electrode resistance, temperature increment in the cathode chamber, current and power consumed by the electric activator for these conditions. Using a three-factor experiment, they have determined optimization criteria: electric activator capacity, its productivity, and operating cycle. The obtained regression equations adequately describe the process of liquid ac tivation in the electric activator and determine the eff ective modes of its operation. It has been experimentally established that effi ciency of water electro-activation process is determined by the value of change in hydrogen index of the activated solution, loss of voltage in the electric activator chamber, and current density determined by the capacity, productivity, and operating cycle of the electric activator.

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Rui Pan, Rui Pan, Rumeng Jiang Rumeng Jiang, and Yao Chen and Jiancheng Zhou Yao Chen and Jiancheng Zhou. "Optimization of the Production of Epichlorohydrin Catalyzed by TS-1 Using the Taguchi Method." Journal of the chemical society of pakistan 45, no. 2 (2023): 93. http://dx.doi.org/10.52568/001210/jcsp/45.02.2023.

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Mass production of Epichlorohydrin (ECH) via epoxidizing allyl chloride suffers from determining the optimal reaction parameters and reproducibility. Titanium silicalite-1 (TS-1) catalyst has been successfully employed to reduce activation energy, but many reaction conditions are involved in the process. To optimize ECH production by analysing its yields, Taguchi method was implemented for reducing time and cost. Included in the reaction parameters were reaction temperature, reaction time and the reactant ratio. This study investigated preparation of heterogeneous catalysts using hydrothermal method and their characterization by XRD, IR, SEM and TEM, which confirmed the presence of ordered MFI structure. Plots of S/N suggested that reaction time was the most influential factor, followed by reaction time in ECH production. The optimum factor parameters were acquired as follows, a reaction time of 40 min, reaction temperature of 90 oC and the molar ratio of H2O2: allyl chloride equal to 1. Aimed at the final confirmation, ECH production experiment was also practiced. Established on the obtained results, the yield of ECH was hugely upgraded to the value of 83.13and#177;1.03 % with only ~0.7% deviated from predicted value.

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Salman, J. M., and F. M. Abid. "Preparation of mesoporous activated carbon from palm-date pits: optimization study on removal of bentazon, carbofuran, and 2,4-D using response surface methodology." Water Science and Technology 68, no. 7 (October 1, 2013): 1503–11. http://dx.doi.org/10.2166/wst.2013.370.

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Palm-date pits were used to prepare activated carbon by physiochemical activation method, which consisted of potassium hydroxide (KOH) treatment and carbon dioxide (CO2) gasification. The effects of variable parameters, activation temperature, activation time and chemical impregnation ratios (KOH: char by weight) on the preparation of activated carbon and for removal of pesticides: bentazon, carbofuran and 2,4-dichlorophenoxyacetic acid (2,4-D) were investigated. Based on the central composite design (CCD), two factor interaction (2FI) and quadratic models were respectively employed to correlate the effect of variable parameters on the preparation of activated carbon used for removal of pesticides with carbon yield. From the analysis of variance (ANOVA), the most influential factor on each experimental design response was identified. The optimum conditions for preparing activated carbon from palm-date pits were found to be: activation temperature of 850 °C, activation time of 3 h and chemical impregnation ratio of 3.75, which resulted in an activated carbon yield of 19.5% and bentazon, carbofuran, and 2,4-D removal of 84, 83, and 93%, respectively.

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Bill, Jeremiah, Lance Champagne, Bruce Cox, and Trevor Bihl. "Meta-Heuristic Optimization Methods for Quaternion-Valued Neural Networks." Mathematics 9, no. 9 (April 23, 2021): 938. http://dx.doi.org/10.3390/math9090938.

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In recent years, real-valued neural networks have demonstrated promising, and often striking, results across a broad range of domains. This has driven a surge of applications utilizing high-dimensional datasets. While many techniques exist to alleviate issues of high-dimensionality, they all induce a cost in terms of network size or computational runtime. This work examines the use of quaternions, a form of hypercomplex numbers, in neural networks. The constructed networks demonstrate the ability of quaternions to encode high-dimensional data in an efficient neural network structure, showing that hypercomplex neural networks reduce the number of total trainable parameters compared to their real-valued equivalents. Finally, this work introduces a novel training algorithm using a meta-heuristic approach that bypasses the need for analytic quaternion loss or activation functions. This algorithm allows for a broader range of activation functions over current quaternion networks and presents a proof-of-concept for future work.

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Ayele, Ashagrie Liyew, Belachew Zegale Tizazu, and Abrham Bayeh Wassie. "Chemical Modification of Teff Straw Biomass for Adsorptive Removal of Cr (VI) from Aqueous Solution: Characterization, Optimization, Kinetics, and Thermodynamic Aspects." Adsorption Science & Technology 2022 (April 15, 2022): 1–25. http://dx.doi.org/10.1155/2022/5820207.

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Teff straw, a by-product of Teff, mainly available in Ethiopia, has not been studied much for biosorbent production. The present study has investigated the effects of modification and optimization of process parameters (viz., concentration of modifying agent (H3PO4 and KOH), modifying temperature, and modifying time) on the Cr (VI) removal efficiency of using chemically activated Teff straw biosorbent by RSM followed by BBD. The maximum Cr (VI) removal was obtained using an H3PO4-modified Teff straw biosorbent of 92.5% with 2 M concentration of the modifying agent, 110°C, and 4 h. Similarly, maximum Cr (VI) removal using KOH-modified Teff straw biosorbent of 95.2% was obtained with 1.5 M activating agent concentration, 105°C activation temperature, and 3.5 h activation time. In addition, the effects of adsorption parameters (viz., biosorbent dosage, temperature, initial concentration of Cr (VI), and contact time) were investigated. The maximum removal efficiency was attained at 2 g of biosorbent dosage, 4 h contact, 75 mg/L of initial Cr (VI) concentration, and 25°C sorption temperature. In addition, isotherm, kinetic, and thermodynamic studies for Cr (VI) biosorption were studied. The experimental adsorption data were well fitted with the Langmuir isotherm and pseudo-second-order kinetic model with higher correlation coefficient in both untreated and chemically modified Teff straw biosorbent. The investigated thermodynamic parameters ( Δ H o , Δ S o , and Δ G o ) confirmed that Cr (VI) metal ions’ adsorption process onto Teff straw biosorbent was spontaneous and endothermic.

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Fungaro, Denise Alves, and Tharcila Bertolini. "Optimization of Pelleting Parameters for Producing Composite Pellets Using Zeolitic Material From Fly Ash." Journal of Applied Materials and Technology 3, no. 2 (January 5, 2023): 13–23. http://dx.doi.org/10.31258/jamt.3.2.13-23.

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Zeolitic material in powder form was prepared from fly ash by direct activation treatment. The resulted fly ash-based zeolite was pelletizing and the effect of different inorganic (calcium hydroxide, bentonite, kaolinite) and organic (dextrin) binders with varying percentage was investigated. The zeolitic materials were analyzed by XRF, XRD, SEM, FTIR, TG-DTG and Nitrogen adsorption/desorption isotherm. Compression and impact tests have been used to study the deformation and breakage behaviour of spherical granules. The best performance was obtained by zeolite granular containing 5 wt.% bentonite and 5 wt.% kaolinite with mechanical strength and satisfactory water resistance. The synthesis of pelletized zeolite from by-products derived from coal combustion provides not only environmental and economic benefits, but also contributes to achieving the principles of sustainable development.

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Ray, Aditi, Joydipta Banerjee, T. R. G. Kutty, Arun Kumar, and Srikumar Banerjee. "Construction of master sintering curve of ThO2 pellets using optimization technique." Science of Sintering 44, no. 2 (2012): 147–60. http://dx.doi.org/10.2298/sos1202147r.

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Sintering kinetics and densification behavior of pure ThO2 have been studied using high temperature dilatometer experiments at constant rate of heating. Sintering activation energy has been determined by Wang and Raj method. Master sintering curve (MSC) for densification is a functional sintering model that describes densification under arbitrary time temperature excursion of a particular material during sintering. MSC for pure ThO2 has been constructed by fitting experimental relative density versus work of sintering data with modified sigmoid function. Five independent parameters of the fitting function are determined by Nelder-Mead optimization technique with the objective of minimizing fitting error in terms of mean residual square. A FORTRAN program has been developed for efficient construction of best converged master curve. It is shown that activation energy of pure ThO2 found by MSC approach is consistent with those obtained by other methods.

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Kouotou, Daouda, Horace Ngomo Manga, Abdelaziz Baçaoui, Abdelrani Yaacoubi, and Joseph Ketcha Mbadcam. "Optimization of Activated Carbons Prepared byH3PO4and Steam Activation of Oil Palm Shells." Journal of Chemistry 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/654343.

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In this study, activated carbons were prepared from oil palm shells by physicochemical activation. The methodology of experimental design was used to optimize the preparation conditions. The influences of the impregnation ratio (0.6–3.4) and the activation temperature between 601°C and 799°C on the following three responses: activated carbon yield (R/AC-H3PO4), the iodine adsorption (I2/AC-H3PO4), and the methylene blue adsorption (MB/AC-H3PO4) results were investigated using analysis of variance (ANOVA) to identify the significant parameters. Under the experimental conditions investigated, the activation temperature of 770°C and impregnation ratio of 2/1 leading to the R/AC-H3PO4of 52.10%, theI2/AC-H3PO4of 697.86 mg/g, and the MB/AC-H3PO4of 346.25 mg/g were found to be optimum conditions for producing activated carbon with well compromise of desirability. The two factors had both synergetic and antagonistic effects on the three responses studied. The micrographs of activated carbons examined with scanning electron microscopy revealed that the activated carbons were found to be mainly microporous and mesoporous.

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Gu, Jie, Cheng Tung Chong, Guo Ren Mong, Jo-Han Ng, and William Woei Fong Chong. "Determination of Pyrolysis and Kinetics Characteristics of Chicken Manure Using Thermogravimetric Analysis Coupled with Particle Swarm Optimization." Energies 16, no. 4 (February 15, 2023): 1919. http://dx.doi.org/10.3390/en16041919.

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The valorization of chicken manure via pyrolysis can give biowaste a second life to generate value and contribute to the circular economy. In the present study, the thermal degradation and pyrolysis characteristics of chicken manure pyrolysis were investigated via thermogravimetric analyses (TGA) coupled with optimization methods. Thermogravimetric data were obtained for the samples at five heating rates of 5, 10, 20, 30 and 50 °C/min over a range of temperature under inert conditions. The manure devolatilization process was initiated at between 328 and 367 °C to overcome the global activation energy barrier. The determined activation energy of the manure via Flynn–Wall–Ozawa (FWO), Kissinger–Akahira–Sunose (KAS), Friedman and Kissinger methods was in the range of 167.5–213.9 kJ/mol. By using the particle swarm optimization (PSO) method, the pyrolytic kinetic parameters of the individual component present in the manure were calculated, in which the activation energy for cellulose (227.8 kJ/mol) was found to be higher than that of hemicellulose (119 kJ/mol) and lignin (134.3 kJ/mol). Based on intrinsic transition-state theory, the pre-exponential factor and activation energy of the manure can be correlated through a linear equation ln Aα = 0.2006 Eα − 1.2847. The devolatilization characteristics of the chicken manure were elucidated via the optimization process, paving the way for the design of thermochemical conversion reactors and processes.

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Rahmati, E., M. Salehi Barough, M. H. Choopan Dastjerdi, and J. Mokhtari. "Design of an out-of-tank neutron beam line for prompt gamma neutron activation analysis at low-power Miniature Neutron Source Reactor." Journal of Instrumentation 18, no. 09 (September 1, 2023): P09036. http://dx.doi.org/10.1088/1748-0221/18/09/p09036.

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Abstract Research reactors are strong and stable neutrons sources, and various researches and applications were carried out using their neutron and gamma beamlines. Some research reactors, such as Miniature Neutron Source (MNSR) Reactors, do not have beam tube in their original design, which can be considered as a disadvantage. The design and installation of beamlines can develop their applications. In this research, the design and optimization of a suitable neutron beamline for PGNAA is done at Isfahan MNSR. Designs are done to reach the appropriate neutron beam parameters and taking into account the geometrical limitations of the MNSR. Neutron beam parameters including thermal neutron flux, thermal to total neutron flux, and thermal neutron flux to gamma dose ratio are considered. For this, vertical beamlines with different diameters are simulated and the optimal diameter is determined. Also, for optimization of beam parameters, a thermal column and gamma filter are considered and optimal conditions are determined.

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Okewale, A. O., and A. T. Adebayo. "Thermodynamic and Optimization Studies of Castor Leaf Extract as Corrosion Inhibitor on Stainless Steel (301)." Nigerian Journal of Technological Development 17, no. 3 (October 29, 2020): 229–38. http://dx.doi.org/10.4314/njtd.v17i3.10.

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Inhibition of stainless steel corrosion in acidic medium with castor leaf extract was studied using the Gravimetric measurement. The mechanisms of inhibition, influence of temperature on inhibition efficiency and weight loss were determined for temperature range 40 oC – 80 oC at 7 hours immersion time. An increased in temperature showed a decreased in the inhibition efficiency of the castor leaf extract which resulted to increase in weight loss of the stainless steel. The value of rate constant for the corrosion process ranges from 0.333 – 1.225 hr−1, this is seen to be directly relative to the inhibitor concentrations. Activation energy, enthalpy of activation, and entropy values ranges from 74.000 - 136.377 kJ/mol, 71.820 – 133.620 kJ/mol, and 9.860 – 178.110 J/molK respectively. Rise in activation energy with inhibitor concentration confirmed physisorption adsorption mechanism for stainless steel surface corrosion. In order to obtain the optimum weight loss, optimization of the process variables was carried out using the Box – Behnken Design plan and desirability function of response surface methodology (RSM). Four parameters were varied viz; time of immersion, HCl concentration, inhibitor’s concentration, and temperature alongside their effects on weight loss of the stainless steel were verified. The optimal conditions predicted from the second order quadratic model were time (9.10 hours), HCl concentration (3.97 M), concentration of inhibitor (240.90 ppm), and temperature (78.67 oC) with 2.978 g as the weight loss. Statistically, the results showed that 95.03% of the variation in total weight loss of stainless steel can be connected to the experimental variables examined. Keywords: Weight loss, activation parameters, adsorption, optimization, stainless steel, castor leaf

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Li, Qing, Yu-Qiang Shao, Huan-Ling Liu, and Xiao-Dong Shao. "Multi-Objective Optimization of Activation Time and Discharge Time of Thermal Battery Using a Genetic Algorithm Approach." Energies 13, no. 24 (December 8, 2020): 6477. http://dx.doi.org/10.3390/en13246477.

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Activation time and discharge time are important criteria for the performance of thermal batteries. In this work a heat transfer analysis is carried out on the working process of thermal batteries. The effects of the thicknesses of heat pellets which are divided into three groups and that of the thickness of insulation layers on activation time and discharge time of thermal batteries are numerically studied using Fluent 15.0 when the sum of the thickness of heating plates and insulation layers remain unchanged. According to the numerical results, the optimal geometric parameters are obtained by using multi-objective genetic algorithm. The results show that the activation time is mainly determined by the thickness of the bottom heat pellet, while the discharge time is determined by the thickness of the heat pellets and that of the insulation layers. The discharge time of the optimized thermal battery is increased by 4.08%, and the activation time is increased by 1.23%.

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Сергеенко, С. Н., А. Н. Васильев, and Д. В. Василенко. "Multicriteria optimization of technological parameters for obtaining composite material Pb-C and carbon coating." Informacionno-technologicheskij vestnik, no. 3(25) (September 17, 2020): 166–74. http://dx.doi.org/10.21499/2409-1650-2020-25-3-166-174.

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Предложена методика и проведена многокритериальная оптимизация значений технологических факторов получения порошкового композиционного материала Pb-C и углеродных покрытий. Определены оптимальные значения: - содержания и типа армирующих нитей, обеспечивающих повышенный комплекс механических свойств при минимальном содержании армирующих нитей; - содержания графита и продолжительности механической активации шихты, обеспечивающих повышенные значения прочности на срез и твердости композиционного материала Pb-C электрода свинцово-кислотного аккумулятора при утилизации отходов. На основе проведенной многокритериальной оптимизации предложены улучшенные технологические схемы изготовления композитов. A technique is proposed and a multicriteria optimization of the values of technological factors for obtaining a powder composite material Pb-C and carbon coatings is carried out. The optimal values have been determined: - the content and type of reinforcing threads, providing an increased set of mechanical properties with a minimum content of reinforcing threads; - the graphite content and the duration of the mechanical activation of the mixture, providing increased values of shear strength and hardness of the composite material Pb-C lead-acid battery electrode during waste disposal. Basierend auf der Multikriteria-Optimierung werden verbesserte technologische Schemata für die Herstellung von Verbundwerkstoffen vorgeschlagen.

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Niroula, S., C. Chaudhary, A. Subedi, and B. S. Thapa. "Parametric Modelling and Optimization of Alkaline Electrolyzer for the Production of Green Hydrogen." IOP Conference Series: Materials Science and Engineering 1279, no. 1 (March 1, 2023): 012005. http://dx.doi.org/10.1088/1757-899x/1279/1/012005.

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Abstract Electrolysis is the process of decomposition of the liquid, containing ions by passing electricity through it. This process is achieved by an electrolyzer. An alkaline water electrolyzer uses electrical energy to break the chemical bond between hydrogen and oxygen in an alkaline electrolytic medium. The performance of the electrolyzer depends upon various parameters like temperature, pressure, ohmic overpotential, activation overpotential, etc. In this study, various parameters that affect the performance of the electrolyzer are identified and integrated using fundamental thermodynamics and electrochemical equations. A mathematical model is created in MATLAB/SIMULINK to analyse the voltage vs current density plot of the electrolyzer. An attempt is made to optimize the performance of the electrolyzer through the variation of the parameters. It was observed that increasing the operating temperature and decreasing the operating pressure favours the electrolysis process. Also, 30 wt% of KOH solution as electrolyte exhibits the optimal cell voltage as compared to 20 and 40 wt% solutions.

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Ogbeh, Gabriel, Ayodele O. Ogunlela, and Nicholas O. Emaikwu. "Statistical optimization of iodine adsorption for <i>Pentaclethra macrophylla</i> pods activated carbon production." Science World Journal 18, no. 4 (January 16, 2024): 678–93. http://dx.doi.org/10.4314/swj.v18i4.22.

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Efficient production of activated carbon (AC) depends on variables such as feedstock properties, preparation conditions, and activating agents. This study aimed to identify optimal conditions for AC production from African Oil Bean (Pentaclethra macrophylla) Pods (PMps) using potassium hydroxide (KOH) and phosphoric acid (H3PO4) as activating agents. Through a systematic iodine adsorption characterization approach and leveraging Response Surface Methodology as a chemometric tool, the study fine-tuned chemical activation and carbonization parameters (temperature, time, and impregnation ratio) for producing PMACs. The adjustments directly impacted the iodine number (In) and yields (Cy) of the PMACs (PMAC-KOHop and PMAC-H3PO4op). The predicted In and Cy values closely aligned with the observed values – (PMAC-KOHop: 918.58 mg/g predicted vs. 916.56 mg/g observed; PMAC-H3PO4op: 593.44 mg/g predicted vs. 592.88 mg/g observed) and (PMAC-KOHop: 39.60% predicted vs. 39.15% observed; PMAC-H3PO4op: 51.30% predicted vs. 51.10% observed), demonstrating precision of the production process. Key structural properties, including BET specific surface areas (SSA), total pore volumes (Vt), and average pore diameters, exhibited notable differences between the PMAC-KOHop and PMAC-H3PO4op, with the former demonstrating superiority. Particularly, FTIR spectra highlighted higher aromaticity in PMAC-KOHop, revealing the preference for KOH over H3PO4 in the chemical activation of PMps. The high In achieved with the PMAC-KOHop indicated its efficacy as a pollutant adsorbent, aligning with the established attributes of commercial granular activated carbons for pollutants removal from wastewater. This study establishes PMps as a dependable AC precursor, emphasizing the advantages of KOH over H3PO4 in chemical activation. Future research should be directed at investigating PMAC-KOHop adsorption capabilities for diverse pollutants and exploring PMps' potential contributions to metallic or nanocomposite formations with other adsorbents.

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Sinniha, Shobana, Zaira Zaman Chowdhury, Ahmad Ibn Ibrahimy, Mostak Ahmed, Mohd Rafie Bin Johan, Mayeen Uddin Khandaker, Irfan Anjum Badaruddin, Sarfaraz Kamangar, and Mohamed Hussien. "Two step synthesis and application of porous carbon for removal of copper (II) from wastewater: Statistical optimization and equilibrium isotherm analysis." BioResources 19, no. 2 (April 25, 2024): 3699–724. http://dx.doi.org/10.15376/biores.19.2.3699-3724.

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In this study, activated carbon (ACs) adsorbent was synthesized using the lignocellulosic waste (LCB) seed from Adansonia digitata L. (BSP) using two steps of hydrothermal carbonization (HTC) followed by activation. The hydrothermally produced char of BSP was activated to produce porous activated carbon BSPAC, where K2CO3 was used as a chemical activating agent. Box Behnken Design was used to optimize the input variables of pyrolysis temperature (A1), residence time (B1), and ratio (C1) for the pyrolysis process. Removal percentage (β1), percentage carbon yield (β2), and fixed carbon (β3) percentage were chosen as output responses. The analysis of variance was utilized to generate appropriate mathematical models with subsequent statistical analysis. Physiochemical characterizations were carried out for the hydrothermally carbonized sample (BSPC) and the optimized activated sample (BSPAC). Langmuir, Freundlich, and Temkin models were employed to estimate the isotherm model parameters. The results demonstrated that HTC with subsequent mild activation using K2CO3 can be considered as a greener route to obtain better-quality porous carbon having surface area of 599 m2/gm for removal of Cu(II) cations from wastewater.

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Kalliola, Jussi, Jurgita Kapočiūtė-Dzikienė, and Robertas Damaševičius. "Neural network hyperparameter optimization for prediction of real estate prices in Helsinki." PeerJ Computer Science 7 (April 19, 2021): e444. http://dx.doi.org/10.7717/peerj-cs.444.

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Accurate price evaluation of real estate is beneficial for many parties involved in real estate business such as real estate companies, property owners, investors, banks, and financial institutes. Artificial Neural Networks (ANNs) have shown promising results in real estate price evaluation. However, the performance of ANNs greatly depends upon the settings of their hyperparameters. In this paper, we apply and optimize an ANN model for real estate price prediction in Helsinki, Finland. Optimization of the model is performed by fine-tuning hyper-parameters (such as activation functions, optimization algorithms, etc.) of the ANN architecture for higher accuracy using the Bayesian optimization algorithm. The results are evaluated using a variety of metrics (RMSE, MAE, R2) as well as illustrated graphically. The empirical analysis of the results shows that model optimization improved the performance on all metrics (reaching the relative mean error of 8.3%).

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Zhang, Xukun, Pu Xing, Shengping Liu, Chengzhen Zhang, and Weiliang Fu. "Kinetics of Sludge Superheated Steam Drying and Optimization of Process Parameters." Advances in Materials Science and Engineering 2022 (September 5, 2022): 1–17. http://dx.doi.org/10.1155/2022/3103710.

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The purpose of this paper is to study the effects of steam temperature, sludge thickness, and steam flow on the drying characteristics and drying kinetics of sludge superheated steam and optimize the process parameters of sludge superheated steam drying by using the response surface method and taking relative unit energy consumption as the response value. Single-factor test of superheated steam drying of sludge was conducted under different drying conditions of steam temperature (180, 195, 220, and 260°C), sludge thickness (2, 3.5, 6, and 10 mm), and steam flow rate (22, 29, 36, and 40 m3/h). Taking relative unit energy consumption as the response value and steam temperature, sludge mass (corresponding to sludge thickness), and steam flow as the test factors, the three-factor and five-level response surface test was conducted on the sludge. The experimental results show that steam temperature and sludge thickness had a significant influence on the drying characteristics of superheated sludge steam ( p < 0.05 ). With the increase of steam temperature, the decrease of sludge thickness, and the increase of steam flow, the drying time of sludge will be shortened, the drying efficiency of sludge will be improved, and the maximum condensation amount and recovery time will be reduced. The quadratic polynomials, linear equation, and logarithmic model can better fit the change law of water variation of the sludge of superheated steam condensation section, recovery section, and drying section. With the increase of steam temperature, sludge thickness, and steam flow rate, the effective diffusion coefficient also increases. The activation energy of sludge superheated steam drying was 13.42 kJ/mol at a sludge thickness of 6 mm, steam flow rate of 22 m3/h, and different steam temperatures. The order of influence degree of three test factors on relative unit energy consumption is as follows: sludge mass (corresponding to sludge thickness) > steam flow rate > steam temperature. According to response surface test analysis, the optimal drying process with relative unit energy consumption is steam temperature of 215°C, sludge mass of 25 g (corresponding sludge thickness of 8 mm), and steam flow of 30 m3/h. Under this drying process parameter, the minimum energy consumption of sludge superheated steam drying is 284.61 kJ/g. Compared with the relative unit energy consumption value obtained in the verification test, the relative error is 1.65%.

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Rosales, Gustavo D., Alexander C. J. Resentera, Rodolfo G. Wuilloud, Mario H. Rodriguez та Marcelo R. Esquivel. "Optimization of combined mechanical activation-leaching parameters of low-grade α-spodumene/NaF mixture using response surface methodology". Minerals Engineering 184 (червень 2022): 107633. http://dx.doi.org/10.1016/j.mineng.2022.107633.

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Mani, Thilakavathi, Pulikesi Murugan, and Nader Mahinpey. "Determination of Distributed Activation Energy Model Kinetic Parameters Using Simulated Annealing Optimization Method for Nonisothermal Pyrolysis of Lignin." Industrial & Engineering Chemistry Research 48, no. 3 (February 4, 2009): 1464–67. http://dx.doi.org/10.1021/ie8013605.

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Hu, Xufei, Yiren Fan, Hui Sun, Lei Wang, and Zhenguan Wu. "A novel efficient inversion method for three-dimensional NMR and the optimization of activation sequences and acquisition parameters." Computational Geosciences 22, no. 3 (February 22, 2018): 867–83. http://dx.doi.org/10.1007/s10596-018-9730-z.

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Tuna, Özlem, and Esra Bilgin Simsek. "Promoted peroxymonosulfate activation into ferrite sites over perovskite for sunset yellow degradation: Optimization parameters by response surface methodology." Optical Materials 142 (August 2023): 114122. http://dx.doi.org/10.1016/j.optmat.2023.114122.

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Saneei, Mojtaba, Sayed Amir Hossein Goli, and Javad Keramat. "Optimization of oil bleaching parameters, using response surface methodology, for acid-activated sepiolite from Iran." Clay Minerals 50, no. 5 (December 2015): 639–48. http://dx.doi.org/10.1180/claymin.2015.050.5.07.

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AbstractAn Iranian sepiolite was activated with 1.5 M HCl. During activation, the specific surface area increased from 105 to 168 m2/g and the SiO2 content increased from 45.4 to 51.6%. The roles of temperature and time and the amount of acid-activated sepiolite used, were investigated and the optimum conditions, where chlorophyll, β-carotene, free fatty acid and peroxide were at their minimum levels, were determined for bleaching of canola oil by applying response surface methodology (RSM). Optimum bleaching conditions were obtained by adding 3% of acid-activated sepiolite at a temperature of 110°C with a bleaching time of 42.46 min during which, the amount of chlorophyll-α, β-carotene, free fatty acid and peroxide were reduced from 12.30 to 0.35 mg/kg, 49.15 to 14.98 mg/kg, 0.62 to 0.15%, and 3.87 to 2.14 meq O2/kg of oil, respectively. At optimum conditions, sepiolite displayed a greater capacity for removal of chlorophyll and β-carotene than a commercial bentonite bleaching agent.

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Barkalov, Konstantin, Irek Gubaydullin, Evgeny Kozinov, Ilya Lebedev, Roza Faskhutdinova, Azamat Faskhutdinov, and Leniza Enikeeva. "On Solving the Problem of Finding Kinetic Parameters of Catalytic Isomerization of the Pentane-Hexane Fraction Using a Parallel Global Search Algorithm." Mathematics 10, no. 19 (October 6, 2022): 3665. http://dx.doi.org/10.3390/math10193665.

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This article is devoted to the problem of developing a kinetic model of a complex chemical reaction using a parallel optimization method. The design of the kinetic model consists of finding the kinetic parameters of the reaction, which cannot be calculated analytically, and since the chemical reaction involves many stages, the optimization problem is multiextremal. As a chemical reaction, the process of catalytic isomerization of the pentane-hexane fraction is considered, which is now important due to the switch of the oil refining industry to the production of gasoline corresponding to the Euro-5 standard. On the basis of known industrial data on the concentrations of reaction components and the temperature at the outlet of the third reactor, the activation energies and pre-exponential factors of each reaction stage were calculated. To solve the optimization problem, the authors developed a parallel global search algorithm and a program based on Lipschitz optimization. The kinetic parameters found made it possible to develop a mathematical model of the process, which is in good agreement with industrial data. The developed mathematical model in future works will make it possible to study the dynamics of the gas–liquid flow in the reactor unit, taking into account diffusion and heat exchange processes through the catalyst layer.

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