Heuristic Model Research Articles

Bacterial cell size modulation along the growth curve across nutrient conditions.

Under stable growth conditions, bacteria maintain cell size homeostasis through coordinated elongation and division. However, fluctuations in nutrient availability result in dynamic regulation of the target cell size. Using microscopy imaging and mathematical modelling, we examine how bacterial cell volume changes over the growth curve in response to nutrient conditions. We find that two rod-shaped bacteria, Escherichia coli and Salmonella enterica, exhibit similar cell volume distributions in stationary phase cultures irrespective of growth media. Cell resuspension in rich media results in a transient peak with a five-fold increase in cell volume ≈ 2h after resuspension. This maximum cell volume, which depends on nutrient composition, subsequently decreases to the stationary phase cell size. Continuous nutrient supply sustains the maximum volume. In poor nutrient conditions, cell volume shows minimal changes over the growth curve, but a markedly decreased cell width compared to other conditions. The observed cell volume dynamics translate into non-monotonic dynamics in the ratio between biomass (optical density) and cell number (colony-forming units), highlighting their non-linear relationship. Our findings support a heuristic model comparing modulation of cell division relative to growth across nutrient conditions and providing novel insight into the mechanisms of cell size control under dynamic environmental conditions.

Validation of a Methodology To Assess The Flutter Limit Cycle Oscillation Amplitude of Low-Pressure Turbine Bladed-Disks - Part II: Rotational Speed Effects

Abstract The effect of the operating conditions on the vibration amplitude trends of an isolated low-pressure turbine rotor is described. The study utilizes an analytical model correlating the aerodynamic and dry-friction work introduced in Part I of the paper. In this Part II, the analysis has been extended to incorporate the influence of rotational speed. The force distribution and the penetration length of the fir-tree contact surfaces are key parameters within the heuristic micro-slip model used to characterize the friction forces. These parameters change with rotational speed, consequently influencing the dry-friction work involved in the process. The model is closed with numerical simulations to compute the aerodynamic damping, and it is compared against experimental data gathered from the experimental campaign detailed in Part I. The results demonstrate a significant impact of the shaft speed on flutter vibration amplitude. The vibration amplitude has been observed to reach a maximum near the on-design conditions. The analytical model can correctly capture this trend indicating that the essential physics is retained in it. Nonlinear friction, mistuning and 3D unsteady aerodynamics have shown to play a predominant role to explain the change of vibration amplitude with the shaft speed.

Sample size effects on landslide susceptibility models: A comparative study of heuristic, statistical, machine learning, deep learning and ensemble learning models with SHAP analysis

In landslide susceptibility assessment (LSA), inventory incompleteness impacts the accuracy of different models to varying degrees. However, this area remains under-researched. This study investigated six LSA models from heuristic, statistical, machine learning and ensemble learning models (analytical hierarchy process (AHP), frequency ratio (FR), logistic regression (LR), Keras based deep learning (KBDL), XGBoost, and LightGBM) across six different sample sizes (100%, 90%, 75%, 50%, 25%, and 10%). Results revealed that XGBoost and LightGBM consistently outperformed other models across all sample sizes. The LR and KBDL models followed, while FR model was the most affected by sample size variations. AHP, an empirical model, remained unaffected by sample size. Through SHapley Additive exPlanations (SHAP) analysis, elevation, NDVI, slope, land use, and distance to roads and rivers emerged as pivotal indicators for landslide occurrences in the study area, suggesting that human activities significantly influence these events. Five time-varying indicators regarding human activity and climate validated this inference, which provides a new method to identify landslide triggering factors, especially in areas of intense human activity. Based on the findings, a comprehensive framework for LSA is proposed to assist landslide managers in making informed decisions. Future research should focus on expanding model diversity to address the effects of sample size, enhancing the adaptability of the LSA framework, deepening the analysis of human activity impacts on landslides using explainable machine learning techniques, addressing temporal inventory incompleteness in LSA, and critically evaluating model sensitivity to sample size variations across multiple disciplines.

Rethinking Lifetime Abuse in Old Age.

Research on abuse is often piecemeal and focused on specific forms, populations, and social situations. As a result, these studies tend to ignore the web of abuse resulting from the interactive effects of various forms of abuse over the life course, together referred to as "lifetime abuse." An examination of abuse from the point of view of older adults is likely to provide a lifetime perspective based on linking child abuse to elder abuse over the life course and an assessment of its consequences. Despite the growing awareness and resulting body of knowledge regarding this phenomenon, proposed theoretical formulations about it remain limited. The present article aimed to conceptualize the multifaceted phenomenon of lifetime abuse and to gain a deeper perspective of the topic by understanding its dimensions, meanings, and experiences in older age, based on a critical review of empirical studies. A model is suggested, which can be useful for future exploration and understanding of lifetime abuse. Based on a critical review of previous studies, we suggest a theoretical framework of lifetime abuse from the perspective of older adults, identifying three key domains: (a) perception of time and life review in old age; (b) cumulative and interactive abusive life events; and (c) resilience versus vulnerability over the life course. We propose a heuristic model to explore and understand lifetime abuse. We believe our proposed model is open to reflection and elaboration and is intended to raise questions that could enhance the need for our understanding of lifetime abuse in old age.

The Development of Student Digital Worksheets Based on Logan Avenue Problem Solving (LAPS)-Heuristic to Improve Critical Thinking Skills

This research aims to develop a student digital worksheet product with a valid, practical, and effective model of Logan Avenue Problem Solving (LAPS)-Heuristic . Using the ADDIE model, results show the worksheet enhances critical thinking skills. The validity obtained from the material expert is 92% and based on the media expert is 85.4%. Also, the percentage of practicality is 92.9% and is included in the practical category. Implementation of learning with the application of student digital worksheets Effectiveness was demonstrated with 86.67% of students meeting learning completeness, and a medium improvement in critical thinking skills (gain score: 0.639). From the collected data, it is concluded that the Logan Avenue Problem Solving (LAPS)-Heuristic learning model developed meets the qualifications of valid, practical, and effective.

“Going once, going twice, sold!”: A new look at the auction tilt in public procurement

The paper examines the auction tilt phenomenon in public procurement in terms of the transaction mechanisms of governance. Arguments to develop the discussion on limits of using auctions expediency and consequences of their forced distribution in public sector procurement are proposed. The reasons for maintaining the auction tilt despite the recognition of this practice as vicious in some jurisdictions and its numerous criticisms in the literature are explained. Transaction cost theory tools helped identify the failures of theoretical ideas about the effectiveness of auctions as attempts to bring the governance mechanism closer to the market one. Using heuristic models within the framework of the theory of transaction costs, a mechanism has been demonstrated that promotes the sustainability of the practice of regulated procurement with an auction bias, which is ineffective for a wide class of goods (works, services).

Membaca Pemikiran Orang Jawa Tentang Kesempurnaan Hidup Melalui Teks Piwulang

The Serat Piwulang Kasampurnaning Ngagesang manuscript is one of the Javanese manuscripts that contains the teachings of life. This manuscript is important to study because it contains teachings to achieve perfection in life according to Javanese thinking. The problem in this study is that the Javanese people's thoughts about the perfection of life contained in this manuscript have not been revealed. The purpose of the research is to explore the thoughts of the Javanese people from the source of the text of Serat Piwulang Kasampurnaning Ngagesang which then the results of the description can be known to the general public and can be used as a guideline for the younger generation. This study uses an objective approach, with heuristic and hermeneutic reading models. Heuristic reading is carried out by reading the entire text sourced from the NB 807 manuscript of the National Library of the Republic of Indonesia. Hermeneutic reading is carried out by paying attention to textual, historical and philosophical meanings. The results of the study show that there is a view of the importance of names for human life and the seven things that are desired in life. Javanese people view the name as something important because it is an honor for everyone. Perfection of life for Javanese people is the fulfillment of seven desired things consisting of health and safety, food, shelter, clothing, honor or power, security and peace of mind, sincerity and sustainability. And the key to getting these seven things is to be grateful, patient, praying, and trying. All of it comes from the heart of each one. The heart can have taste, but the taste does not have the heart.

School Violence in the Israeli Arab Educational System: Investigating the Implications of Paternalistic Leadership and teachers’ Job Satisfaction

ABSTRACT School violence is a growing issue that adversely affects learning, academic achievement, and student growth. Drawing upon the heuristic model of school violence proposed by the study proposes to examine the direct and indirect relationship (through teacher satisfaction) between paternalistic leadership (PL) and school violence in the Arab educational system in Israel. The data were collected through a questionnaire returned by a two-stage clusters random sampling of 350 teachers randomly chosen from 70 elementary Israeli Arab schools. Data were collected from three sources: self-reporting (teachers and students) and non-self-reporting to minimize measure error. The Structural Equation Modelling and bootstrap results highlighted that paternalistic leadership was not correlated to teachers’ satisfaction but directly correlated to school violence. The findings also showed positive relationships of teachers’ job satisfaction and lessening school violence levels. Implications for theory and practise are discussed.

Industrial CO2 transport in Germany: Comparison of pipeline routing scenarios

Carbon capture and storage will be necessary for some industries to reach carbon neutrality. One of the main associated challenges is the design of the network linking the CO2 sources to the storage sites. Establishing a CO2 network can be impacted by many uncertainties such as CO2 amounts, pipeline routes and the locations of emitters and carbon sinks. We present a framework to investigate different scenarios of a future CO2 network in Germany. The analyses compare the routes and associated costs of different scenarios. The developed model uses several geospatial datasets and an optimization scheme to yield realistic and cost-efficient outcomes. Parameters such as population density and existing infrastructure are integrated to calculate potential routes, which are then used as an input for the developed heuristic model to determine the optimum network. The derived framework is flexible and can be used for investigating other scenarios, regions and settings. The results show that the different scenarios have a profound impact on the optimal layout and costs. The investment costs of the investigated scenarios range between 1.3 and 3 billion EUR. The outcomes are important for academia, industry and policymaking for the ongoing discussions regarding the development of carbon infrastructure.

Estimating the effect of sand-roughened bed on hydraulic jump characteristics using heuristic models

The hydraulic jump occurs in open channels and downstream of hydraulic structures because these features change the flow regime from super-critical to sub-critical. To prevent downstream channel erosion and guarantee the construction of a hydraulic jump, a stilling basin is utilized. The effect of sand-roughened beds on hydraulic jump characteristics was investigated using an experimental study. After that, new machine learning models including Emotional neural network (EANN), Hammerstein Weiner model (HWM), Elman neural networks ENN, and Extreme learning neural networks (ELNN) were adopted to estimate the ratio of hydraulic jump length to initial water depth. Different evaluation criteria such as determination Coefficient (R2), Mean Square Error (MSE), Correlation Coefficient (R), and Rout Mean Square Error (RMSE), scatter plots, time series comparison, and Spiral plots have been used to evaluate the models' performance. The results revealed that the Elman NN model outperformed the other models in estimating the ratio of hydraulic jump length to the initial depth (Lj/y1), while the HWM model has a weaker performance than other models in estimating Lj/y1.

Stochastic heuristics for decisions under risk and uncertainty.

Models of heuristics are often predicated on the desideratum that they should possess no free parameters. As a result, heuristic implementations are usually deterministic and do not allow for any choice errors, as the latter would require a parameter to regulate the magnitude of errors. We discuss the implications of this in light of research that highlights the evidence supporting stochastic choice and its dependence on preferential strength. We argue that, in principle, the existing models of deterministic heuristics should, and can, be quite easily modified to stochastic counterparts through the addition of an error mechanism. This requires a single free parameter in the error mechanism, whilst otherwise retaining the parameter-free cognitive processes in the deterministic component of existing heuristics. We present various types of error mechanisms applicable to heuristics and discuss their comparative virtues and drawbacks, paying particular attention to their impact on model comparisons between heuristics and parameter-rich models.

Pattern Theory of Selflessness: How Meditation May Transform the Self-Pattern

For many centuries, scholars and philosophers from wisdom traditions in different cultures have reported and discussed non-self states of consciousness. These states can be both short-term (state, transitory) and long-term (trait, lasting) conditions. However, in psychology, the importance of a healthy self is usually emphasized, and some theorists have dismissed the idea of “selfless” modes of functioning. This disagreement hinders further empirical progress in the study of self and the way it might be affected by meditation. This paper addresses this issue by providing an interdisciplinary conceptual discussion, grounded in the pattern theory of self (PTS). According to PTS, what we call “self” is a complex pattern of dynamically related constituent processes, which include embodied, experiential (prereflective), affective, psychological/cognitive, reflective, narrative, intersubjective, ecological, and normative processes. We propose that Buddhist and secular meditative practices induce a reorganization of the self-pattern, allowing individuals to experience a “selfless” state, both temporarily and persistently. We then put forward a heuristic model, the pattern theory of selflessness (PTSL), possibly experienced through meditation practices. The proposed PTSL model consists of six transformations that contribute to self-pattern reorganization in a nonlinear and iterative manner: consolidating and integrating the self-pattern; cultivating concentration and present-moment awareness; cultivating mindful awareness; self-deconstruction (non-self) states; self-flexibility; and self-liberation as a trait. This conceptual analysis and integrative view contributes to the growing field of consciousness and contemplative research by advancing the contemporary understanding of non-self experience and its relation to Buddhist and secular meditation. The proposed model serves as a basis for interdisciplinary efforts to guide empirical research in this area.

Changes in modifiable risk factors in women at increased risk for breast and ovarian cancer during the COVID-19 pandemic

BackgroundModifiable lifestyle factors exert a substantial influence on the development of various diseases. The COVID-19 pandemic necessitated the implementation of containment measures to mitigate the viral spread, which affected the maintenance of healthy habits. MethodsChanges in lifestyle factors (e.g. physical activity, nutrition, smoking, drinking alcohol) within a cohort of German women at increased risk of breast cancer (BC) or ovarian cancer (OC) were evaluated through an anonymous web-based survey. The self-reported assessment of mental health was conducted using the PHQ-4 questionnaire. This tool combines two items from the Patient Health Questionnaire for Depression (PHQ-2) and two queries from the Generalized Anxiety Disorder Scale (GAD-2). Potential predictors of lifestyle changes were determined via multiple logistic regression analysis. A heuristic model was employed to project potential long-term consequences on BC incidence. ResultsDuring the pandemic, 41.6 % of respondents reported reduced engagement in physical activity (PA), whereas 14.3 % reported increased engagement in PA. A score ≥5 on the PHQ-2 scale emerged as an independent risk factor for reduced PA (OR 12.719; 95 % CI 1.089–148.549; p = 0.043). By the heuristic approach, we projected an increase of BC by 3384 cases in Germany by 2030, which is attributable to the alterations in PA patterns during the pandemic. DiscussionImpaired mental health during the pandemic constituted a risk factor for unfavorable changes in PA. Consequently, a surge in BC may arise due to decreased engagement in PA. Healthcare professionals must remain aware of the potential risk factors that facilitate adverse alterations in modifiable risk factors caused by pandemic-related contingency measures or similar future events.

How do care-related beliefs contribute to depression and anxiety in family caregivers of people with dementia? Testing a cognitive vulnerability-stress model

Objectives Care-related beliefs are considered risk factors for decreased mental health in family caregivers of people with dementia. However, their exact role in the caregiver stress process remains unclear. Hence, we tested a cognitive vulnerability-stress model of depression and anxiety in family caregivers of people with dementia. Method A cross-sectional study was conducted using baseline data from a caregiver intervention trial (N = 322). Within Bayesian moderated mediation analysis, we examined mediation of effects of objective demands (severity of dementia, challenging behavior, caregiving intensity, caregiving duration) on depression and anxiety via subjective caregiver burden and moderation by care-related beliefs in four domains (dysfunctional caregiving standards, dysfunctional attitudes towards dementia, functional self-care-related beliefs, functional acceptance-related beliefs). Results The relation between objective demands and subjective burden was amplified by dysfunctional caregiving standards and dysfunctional attitudes towards dementia and mitigated by functional self-care-related beliefs. Further, functional acceptance-related beliefs attenuated the effect of subjective caregiver burden on depression. Conclusion The study provides preliminary evidence for a cognitive vulnerability-stress model of depression and anxiety in family caregivers of people with dementia. The results indicate that the four-domain model of care-related beliefs is a valuable framework for future research and may serve as a heuristic model for cognitive-behavioral therapy in this population.

Identifying critical nodes in interdependent networks by GA-XGBoost

Once a critical node is destroyed, the interdependent network is prone to experience severe cascading failure. Due to the coupling, traditional methods are challenging to apply to interdependent networks. Here, we propose a novel comprehensive model based on machine learning. The main work of this data-driven approach is to train the model on a small set of nodes (5 % of the graph) and do the critical node identification on the rest. We collect node centrality indicators to describe the node features and provide informative input data from different dimensions. The uniform node sampling is improved to cluster oversampling, which combines K-means and Synthetic Minority Over-sampling Technique (SMOTE) to select and recreate uniformly distributed training samples. We optimize the XGBoost based on the Genetic algorithm (GA) to overcome the instability of manual parameters. Kendall's τ correlation coefficient, Jaccard similarity coefficient, R2, and RMSE are used as the model performance evaluation metrics. Experiment results confirm that the proposed GA-XGBoost model outperforms others, demonstrating higher adaptability and stability in various situations. The heuristic algorithm-optimized machine learning model offers a viable solution for identifying critical nodes in interdependent networks, which is of great significance for controlling virus propagation and preventing failures.

Bipedalism or bipedalisms: The os coxae of StW 573.

There has been a long debate about the possibility of multiple contemporaneous species of Australopithecus in both eastern and southern Africa, potentially exhibiting different forms of bipedal locomotion. Here, we describe the previously unreported morphology of the os coxae in the 3.67 Ma Australopithecus prometheus StW 573 from Sterkfontein Member 2, comparing it with variation in ossa coxae in living humans and apes as well as other Plio-Pleistocene hominins. Statistical comparisons indicate that StW 573 and 431 resemble humans in their anteroposteriorly great iliac crest breadth compared with many other early australopiths, whereas Homo ergaster KNM WT 15000 surprisingly also has a relatively anterioposteriorly short iliac crest. StW 573 and StW 431 appear to resemble humans in having a long ischium compared with Sts 14 and KNM WT 15000. A Quadratic Discriminant Function Analysis of morphology compared with other Plio-Pleistocene hominins and a dataset of modern humans and hominoids shows that, while Lovejoy's heuristic model of the Ardipithecus ramidus os coxae falls with Pongo or in an indeterminate group, StW 573 and StW 431 from Sterkfontein Member 4 are consistently classified together with modern humans. Although clearly exhibiting the classic "basin shaped" bipedal pelvis, Sts 14 (also from Sterkfontein), AL 288-1 Australopithecus afarensis, MH2 Australopithecus sediba and KNM-WT 15000 occupy a position more peripheral to modern humans, and in some analyses are assigned to an indeterminate outlying group. Our findings strongly support the existence of two species of Australopithecus at Sterkfontein and the variation we observe in os coxae morphology in early hominins is also likely to reflect multiple forms of bipedality.

Effects of Heuristic Method on Students’ Performance in Mathematics

This research determines the effects of the Heuristic method on students' performance in Mathematics 7 of a public national high school in the Philippines, school year 2022-2023. The quasi-experimental method used two sets of questionnaires (standardized Attitudes Towards Mathematics Inventory and standardized Algebra Test). The data were treated using frequency, mean, standard deviation, Chi-square test of independence, and paired t-test. The study revealed that student’s profiles (age, gender, final grade in Grade 6 Math) do not have significant relationships with their level of mathematical attitudes and academic performance. However, a significant increase in test scores between the pretest and post-test results in a significant difference between the mean gained of both groups. Thus, teaching strategies could encourage students to increase their academic performance. It was concluded that the Heuristic teaching model helps students develop better mathematics learning. The researchers strongly recommend searching for more learning methods that could help elevate the learners' academic performance.

The dynamics of evolutionary branching in an ecological model

Eco-evolutionary modelling involves the coupling of ecological equations to evolutionary ones. The interaction between ecological dynamics and evolutionary processes is essential to simulating evolutionary branching, a precursor to speciation. The creation and maintenance of biodiversity in models depends upon their ability to capture the dynamics of evolutionary branching. Understanding these systems requires low-dimension models that are amenable to analysis. The rapid reproduction rates of marine plankton ecosystems and their importance in determining the fluxes of climatically important gases between the ocean and atmosphere suggest that the next generation of global climate models needs to incorporate eco-evolutionary models in the ocean. This requires simple population-level models, that can represent such eco-evolutionary processes with orders of magnitude fewer equations than models that follow the dynamics of individual phenotypes. We present a general framework for developing eco-evolutionary models and consider its general properties. This framework defines a fitness function and assumes a beta distribution of phenotype abundances within each population. It simulates the change in total population size, the mean trait value, and the trait differentiation, from which the variance of trait values in the population may be calculated. We test the efficacy of the eco-evolutionary modelling framework by comparing the dynamics of evolutionary branching in a six-equation eco-evolutionary model that has evolutionary branching, with that of an equivalent one-hundred equation model that simulates the dynamics of every phenotype in the population. The latter model does not involve a population fitness function, nor does it assume a distribution of phenotype abundance across trait values. The eco-evolutionary population model and the phenotype model produce similar evolutionary branching, both qualitatively and quantitatively, in both symmetric and asymmetric fitness landscapes. In order to better understand the six-equation model, we develop a heuristic three-equation eco-evolutionary model. We use the density-independent mortality parameter as a convenient bifurcation parameter, so that differences in evolutionary branching dynamics in symmetric and asymmetric fitness landscapes may be investigated. This model shows that evolutionary branching of a stable population is flagged by a zero in the local trait curvature; the trait curvature then changes sign from negative to positive and back to negative, along the solution. It suggests that evolutionary branching points may be generated differently, with different dynamical properties, depending upon, in this case, the symmetry of the system. It also suggests that a changing environment, that may change attributes such as mortality, could have profound effects on an ecosystem’s ability to adapt. Our results suggest that the properties of the three-dimensional model can provide useful insights into the properties of the higher-dimension models. In particular, the bifurcation properties of the simple model predict the processes by which the more complicated models produce evolutionary branching points. The corresponding bifurcation properties of the phenotype and population models, evident in the dynamics of the phenotype distributions they predict, suggest that our eco-evolutionary modelling framework captures the essential properties that underlie the evolution of phenotypes in populations.

Comparison of the Fuzzy Time Series Chen Model and the Heuristic Model in Forecasting the Number of International Tourists in West Sumatra

The Fuzzy Time Series Chen and Heuristic are two forecasting methods based on fuzzy logic used to predict values in time series. The FTS Chen and Heuristic models have almost identical forecasting processes, but the main difference lies in how they develop fuzzy logical relationships. The FTS Chen model uses Fuzzy Logical Relationship Groups obtained from the results of Fuzzy Logical Relationships for the forecasting process. On the other hand, the FTS Heuristic model uses Fuzzy Logical Relationships directly in the forecasting process. Fuzzy Logical Relationships are a collection of fuzzy logical relationships used to connect values in time series. By using Fuzzy Logical Relationships, the Heuristic model can predict values in time series more accurately and effectively. The forecasting is done to plan the development of tourism infrastructure, determine service needs, and optimize tourism promotion. The data shows that the number of foreign tourists visiting West Sumatra has continued to grow from 2006 to 2023. The comparison of the accuracy of the forecasting results of FTS Chen and Heuristic models for foreign tourists in West Sumatra yielded a MAPE of 0.241% for FTS model Chen and 0.194% for FTS model Heuristic. This indicates that the best forecasting model for foreign tourists is the Heuristic model due to its lower MAPE value.

Hybrid Grey Wolf Optimizer for Efficient Maximum Power Point Tracking to Improve Photovoltaic Efficiency

Today, the demand for Renewable Energy (RE) sources has increased a lot; out of all Renewable Energy Sources (RES), Solar Energy (SE) has emerged as a better solution due to its sustainability and abundance. However, energy sources from the sun directly depend on the efficiency of the photovoltaic (PV) systems employed, whose efficiency depends on the variability of solar irradiance and temperature. So harvesting the maximum output from PV panels requires optimized Maximum Power Point Tracking (MPPT) systems. The traditional MPPT systems that involved Perturb and Observe (P&O) and Incremental Conductance (IncCond) are the most widely used models. However, those models have limited efficiency due to rapidly changing environmental conditions and their tendency to oscillate around the Maximum PowerPoint (MPP). This paper proposes a Hybrid Heuristic Model (HHM) called the Hybrid Grey Wolf Optimizer (HGWO) Algorithm, which employs the Genetic Algorithm (GA) model for optimizing the Grey Wolf Optimizer (GWO) algorithm for effectively utilizing MPPT in PV systems. The simulation decreases fluctuation, boosting how the system responds to shifts in the surrounding atmosphere. The framework evolved through several experiments, and its ability to perform was assessed concerning the results of different models for the factors that were considered seriously throughout several solar radiation and temperature scenarios. During all of the tests, the recommended HGWO model scored more effectively than the other models. This succeeded by accurately following the MPP and boosting the power supply.