To see the other types of publications on this topic, follow the link: Intelligence explosion.
Journal articles on the topic 'Intelligence explosion'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Intelligence explosion.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Jebari, Karim, and Joakim Lundborg. "The intelligence explosion revisited." foresight 21, no. 1 (2019): 167–74. http://dx.doi.org/10.1108/fs-04-2018-0042.
Full textAbstract:
Purpose The claim that super intelligent machines constitute a major existential risk was recently defended in Nick Bostrom’s book Superintelligence and forms the basis of the sub-discipline AI risk. The purpose of this paper is to critically assess the philosophical assumptions that are of importance to the argument that AI could pose an existential risk and if so, the character of that risk. Design/methodology/approach This paper distinguishes between “intelligence” or the cognitive capacity of an individual and “techne”, a more general ability to solve problems using, for example, technological artifacts. While human intelligence has not changed much over historical time, human techne has improved considerably. Moreover, the fact that human techne has more variance across individuals than human intelligence suggests that if machine techne were to surpass human techne, the transition is likely going to be prolonged rather than explosive. Findings Some constraints for the intelligence explosion scenario are presented that imply that AI could be controlled by human organizations. Originality/value If true, this argument suggests that efforts should focus on devising strategies to control AI rather strategies that assume that such control is impossible.
2
Prasad, Mahendra. "Nicolas de Condorcet and the First Intelligence Explosion Hypothesis." AI Magazine 40, no. 1 (2019): 29–33. http://dx.doi.org/10.1609/aimag.v40i1.2855.
Full textAbstract:
The intelligence explosion hypothesis (for example, a technological singularity) is roughly the hypothesis that accelerating knowledge or technological growth radically changes humanity. While 20th-century figures are commonly credited as the first discoverers of the hypothesis, I assert that Nicolas de Condorcet, the 18th-century mathematician, is the earliest to (1) mathematically model an intelligence explosion, and (2) present an accelerating historical worldview, and (3) make intelligence explosion predictions that were restated centuries later. Condorcet provides insights on how ontology and social choice can help resolve value alignment.
3
Khan, Amad Ullah, Saad Salman, Khan Muhammad, and Mudassar Habib. "Modelling Coal Dust Explosibility of Khyber Pakhtunkhwa Coal Using Random Forest Algorithm." Energies 15, no. 9 (2022): 3169. http://dx.doi.org/10.3390/en15093169.
Full textAbstract:
Coal dust explosion constitutes a significant hazard in underground coal mines, coal power plants and other industries utilising coal as fuel. Knowledge of the explosion mechanism and the factors causing coal explosions is essential to investigate for the identification of the controlling factors for preventing coal dust explosions and improving safety conditions. However, the underlying mechanism involved in coal dust explosions is rarely studied under Artificial Intelligence (AI) based modelling. Coal from three different regions of Khyber Pakhtunkhwa, Pakistan, was tested for explosibility in 1.2 L Hartmann apparatus under various particle sizes and dust concentrations. First, a random forest algorithm was used to model the relationship between inputs (coal dust particle size, coal concentration and gross calorific value (GCV)), outputs (maximum pressure (Pmax) and the deflagration index (Kst)). The model reported an R2 value of 0.75 and 0.89 for Pmax and Kst. To further understand the impact of each feature causing explosibility, the random forest AI model was further analysed for sensitivity analysis by SHAP (Shapley Additive exPlanations). The study revealed that the most critical parameter affecting the explosibility of coal dust were particle size > GCV > concentration for Pmax and GCV > Particle size > Concentration for Kst. Mutual interaction SHAP plots of two variables at a time revealed that with <200 gm/L concentration, −73 µm size and a high GCV coal was the most explosive at a high concentration (>400 gm/L), explosibility is relatively lower irrespective of GCV and particle sizes.
4
Khan, Amad Ullah, Saad Salman, Khan Muhammad, and Mudassar Habib. "Modelling Coal Dust Explosibility of Khyber Pakhtunkhwa Coal Using Random Forest Algorithm." Energies 15, no. 9 (2022): 3169. http://dx.doi.org/10.3390/en15093169.
Full textAbstract:
Coal dust explosion constitutes a significant hazard in underground coal mines, coal power plants and other industries utilising coal as fuel. Knowledge of the explosion mechanism and the factors causing coal explosions is essential to investigate for the identification of the controlling factors for preventing coal dust explosions and improving safety conditions. However, the underlying mechanism involved in coal dust explosions is rarely studied under Artificial Intelligence (AI) based modelling. Coal from three different regions of Khyber Pakhtunkhwa, Pakistan, was tested for explosibility in 1.2 L Hartmann apparatus under various particle sizes and dust concentrations. First, a random forest algorithm was used to model the relationship between inputs (coal dust particle size, coal concentration and gross calorific value (GCV)), outputs (maximum pressure (Pmax) and the deflagration index (Kst)). The model reported an R2 value of 0.75 and 0.89 for Pmax and Kst. To further understand the impact of each feature causing explosibility, the random forest AI model was further analysed for sensitivity analysis by SHAP (Shapley Additive exPlanations). The study revealed that the most critical parameter affecting the explosibility of coal dust were particle size > GCV > concentration for Pmax and GCV > Particle size > Concentration for Kst. Mutual interaction SHAP plots of two variables at a time revealed that with <200 gm/L concentration, −73 µm size and a high GCV coal was the most explosive at a high concentration (>400 gm/L), explosibility is relatively lower irrespective of GCV and particle sizes.
5
Pratt, Gill A. "Is a Cambrian Explosion Coming for Robotics?" Journal of Economic Perspectives 29, no. 3 (2015): 51–60. http://dx.doi.org/10.1257/jep.29.3.51.
Full textAbstract:
About half a billion years ago, life on earth experienced a short period of very rapid diversification called the “Cambrian Explosion.” Many theories have been proposed for the cause of the Cambrian Explosion, one of the most provocative being the evolution of vision, allowing animals to dramatically increase their ability to hunt and find mates. Today, technological developments on several fronts are fomenting a similar explosion in the diversification and applicability of robotics. Many of the base hardware technologies on which robots depend—particularly computing, data storage, and communications—have been improving at exponential growth rates. Two newly blossoming technologies—“Cloud Robotics” and “Deep Learning”—could leverage these base technologies in a virtuous cycle of explosive growth. I examine some key technologies contributing to the present excitement in the robotics field. As with other technological developments, there has been a significant uptick in concerns about the societal implication of robotics and artificial intelligence. Thus, I offer some thoughts about how robotics may affect the economy and some ways to address potential difficulties.
6
Mirenayat, Sayyed Ali, and Elaheh Soofastaei. "Singularity and Intelligence Explosion in William Hertling’s A.I. Apocalypse." International Letters of Social and Humanistic Sciences 50 (March 2015): 82–85. http://dx.doi.org/10.18052/www.scipress.com/ilshs.50.82.
Full textAbstract:
William Hertling’s A.I. Apocalypse(2012) is a post-apocalyptic novel about vulnerability of modern technological life against superintelligence. The novel shows living in an A.I-controlled society behind a revolution or revolt by self-controlling machines. A personified computer virus infects all the world’s computers. As a result, it leads to disruption in main factors of human life— billions of people are about to die. A novel in which, Hertling warns of dehumanization under the shadow of superintelligence to challenge our minds to ponder about such a future. This study attempts to demonstrate that Hertling criticizes singularity and intelligence explosion in which mankind are entrapped in A.I-controlled society. It also investigates probable bilateral relation between dehumanization and intelligence explosion.
7
Ng, Ho Leung. "Recent Biophysical Advances in Drug Discovery." Biophysica 2, no. 2 (2022): 121–22. http://dx.doi.org/10.3390/biophysica2020013.
Full text
8
Szhydlowski, Alexey V., and Maksim Yu Zadorin. "NATURAL LAW AND ARTIFICIAL INTELLIGENCE: TOWARDS A «DIGITAL CAMBRIAN EXPLOSION»." Bulletin of the Moscow State Regional University (Jurisprudence), no. 3 (2021): 39–53. http://dx.doi.org/10.18384/2310-6794-2021-3-39-53.
Full text
9
Sterelny, Kim. "Social intelligence, human intelligence and niche construction." Philosophical Transactions of the Royal Society B: Biological Sciences 362, no. 1480 (2007): 719–30. http://dx.doi.org/10.1098/rstb.2006.2006.
Full textAbstract:
This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence–ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.
10
Maulana, Yuga, Yuga Maulana, Ganda Marihot Simangunsong, and Tri Karian. "Review Of The Artificial Neural Network Application In Prediciting Blast Vibration." Jurnal GEOSAPTA 7, no. 1 (2021): 47. http://dx.doi.org/10.20527/jg.v7i1.9353.
Full textAbstract:
The blasting method is one of the best hard rock excavation methods in mining activities. This method has negative impacts, one of which is the vibrations generated by the residual energy of the explosion. This impact will affect the environment around the blasting area, both slope stability, tunnels, infrastructure, and human settlements if it is close to the blasting site. Therefore, it needs initial planning and prediction to anticipate the blasting vibration that occurs. In general, the blast vibration can be predicted using the scale distance method which uses two parameters, namely the maximum amount of explosive material per time delay and the distance of measurement from the location of the explosion. This method has been widely researched to produce several empirical equations from each explosion location studied. However, as technology develops, several studies have tried to use artificial intelligence technology, one of which is the artificial neural network algorithm as a new approach for predicting detonation vibrations. In this method, the development of the parameters used in predicting the weighting of the most influential parameters from the formation of detonation vibrations can be carried out. This study will review several studies related to the use of artificial neural networks in predicting blasting vibrations in the studies that have been carried out and also compare with prediction methods using several empirical equations.
11
Mancini, Toni, and Angelo Oddi. "Experimental evaluation of algorithms for solving problems with combinatorial explosion." AI Communications 28, no. 2 (2015): 159–60. http://dx.doi.org/10.3233/aic-140655.
Full text
12
Mancini, Toni, Marco Maratea, and Francesco Ricca. "Experimental evaluation of algorithms for solving problems with combinatorial explosion." AI Communications 29, no. 2 (2016): 245–47. http://dx.doi.org/10.3233/aic-160701.
Full text
13
Du, J. B., Feng Xiong, Tao Yu, and Jun Shi Li. "The Mobile Internet-Based Explosion-Proof LED Lamp Intelligent Lighting System." Applied Mechanics and Materials 743 (March 2015): 728–33. http://dx.doi.org/10.4028/www.scientific.net/amm.743.728.
Full textAbstract:
Systems in the real world are becoming more intelligent, however intelligence has not been widely applied to lighting systems, which are necessary and indispensable parts of human life[1].In this paper, we propose a explosion-proof LED intelligent lighting system for the chemical production, it integrates MCU technology, sensor technology, ZigBee wireless communication technology, WCDMA 3G mobile internet technology, it could overcome the defects of traditional lighting in the chemical production, like poor management, single control, waste of human resources. The level of explosion-proof safety and lighting efficiency will be enhanced.The system could be an instance of intelligent lighting applications.
14
Cepolina, Emanuela Elisa, and Manjula Udayanga Hemapala. "Power Tillers for Demining: Blast Test." International Journal of Advanced Robotic Systems 4, no. 2 (2007): 28. http://dx.doi.org/10.5772/5690.
Full textAbstract:
Power tillers are very simple and versatile machines with large scale diffusion in developing countries, where they are commonly used both for agriculture and for transportation purposes. A new integrated participatory approach that makes use of and improves local end-users knowledge has been used to design a new robotic system for humanitarian demining applications in Sri Lanka, using power tiller as core module. A demining machine composed by a tractor unit, a ground processing tool and a vegetation cutting tool is here presented together with results obtained from the first blast test on the preliminary version of tractor unit armouring. Different breakable connections between wheels and axle have been designed to cause physical detachment and interrupt the transmission of the shock wave released by the explosion of a mine under one wheel. Effects of explosions on different types of wheels and on the chassis have been recorded and commented.
15
Jun, Gao. "The Design of Mine Encapsulated and Intrinsically Safe Explosion-proof Computers." E3S Web of Conferences 248 (2021): 01017. http://dx.doi.org/10.1051/e3sconf/202124801017.
Full textAbstract:
With the continuous improvement of the level of intelligence in coal mines, construction sites have put forward new requirements for the performance and compatibility of mining computers. Aiming at the field conditions of intelligent underground drilling in coal mines, this paper designs a mine-used encapsulated and intrinsically safe computer as a data processing terminal, with the characteristics of a large display screen, a moderate overall weight, powerful operating performance and multiple compatible interfaces, which can replace the explosion-proof and intrinsically safe computers in current field applications.
16
Hu, Xiao, and Hao Wen. "Research on Model Compression for Embedded Platform through Quantization and Pruning." Journal of Physics: Conference Series 2078, no. 1 (2021): 012047. http://dx.doi.org/10.1088/1742-6596/2078/1/012047.
Full textAbstract:
Abstract So far, artificial intelligence has gone through decades of development. Although artificial intelligence technology is not yet mature, it has already been applied in many walks of life. With the explosion of IoT technology in 2019, artificial intelligence has ushered in a new climax. It can be said that the development of IoT technology has led to the development of artificial intelligence once again. But the traditional deep learning model is very complex and redundant. The hardware environment of IoT can not afford the time and resources cost by the model which runs on the GPU originally, so model compression without decreasing accuracy rate so much is applicable in this situation. In this paper, we experimented with using two tricks for model compression: Pruning and Quantization. By utilizing these methods, we got a remarkable improvement in model simplification while retaining a relatively close accuracy.
17
Gavanelli, Marco, and Toni Mancini. "18th RCRA International Workshop on “Experimental evaluation of algorithms for solving problems with combinatorial explosion”." AI Communications 25, no. 2 (2012): 73–74. http://dx.doi.org/10.3233/aic-2012-0528.
Full text
18
Ren, Jiaqi, Shaohui Zhou, Jianyong Wang, Shun Yang, and Chao Liu. "Research on Identification of Natural and Unnatural Earthquake Events Based on AlexNet Convolutional Neural Network." Wireless Communications and Mobile Computing 2022 (August 22, 2022): 1–9. http://dx.doi.org/10.1155/2022/6782094.
Full textAbstract:
Accurately and quickly identifying the types of natural and unnatural earthquake events is the basic premise of monitoring, prediction, early warning, and other study in the field of seismology, which is of great significance to the prevention, evaluation, emergency rescue, and other work of earthquake disasters. Convolutional neural network model is a representative artificial intelligence deep learning algorithm, which has been widely used in computer vision, natural language processing, object type identification, and other fields in recent years. In this study, AlexNet convolutional neural network model is selected to study the type identification of 1539 earthquake event waveform records in and around Ningxia Hui Autonomous Region, China. Earthquake event waveform records contain three types: natural earthquake, explosion, and collapse, in which both explosion and collapse are unnatural earthquakes. MATLAB software is used to build the training module and test module for AlexNet convolutional neural network model, and the earthquake event waveform record is transformed into an image format file of 224 times 224 pixels as input parameters. Finally, AlexNet convolutional neural network model has the ability of automatic identification of earthquake event types. The results of this study show that the identification accuracy of earthquake event type in training module is 99.97%, the average value of loss function is 0.001, the identification accuracy of earthquake event type in test set is 98.51%, and the average value of loss function is 0.059. After training and testing, 60 different types of earthquake event waveform records were randomly selected, and AlexNet convolutional neural network model was used to identify them automatically. The automatic identification accuracy of natural earthquakes, explosions, and collapses was 90%, 80%, and 85%, respectively. After training AlexNet convolutional neural network model with earthquake event waveform records, it can have accurate and fast automatic identification ability. The accuracy of automatic identification is comparable to that of professional seismic workers, and the time of automatic identification is greatly reduced compared with that of professional seismic workers. This study can provide an implementation idea of deep learning based on artificial intelligence for the identification of earthquake event types and make contributions to the cause of earthquake prevention and disaster reduction.
19
Author, Placeholder. "The Population Explosion; Nature's Mind: The Biological Roots of Thinking, Emotions, Sexuality, Language, and Intelligence." Mankind Quarterly 33, no. 2 (1992): 0. http://dx.doi.org/10.46469/mq.1992.33.2.7.
Full text
20
Li, Hong Fei, and Na Wang. "Design of Intelligent Explosion-Proof Electromagnetic Starting Reactor Based on PIC16F887." Applied Mechanics and Materials 143-144 (December 2011): 37–42. http://dx.doi.org/10.4028/www.scientific.net/amm.143-144.37.
Full textAbstract:
According to high-voltage squirrel-cage AC asynchronous motor using string reactor to reduce voltage starting,there are some shortcomings such as circuit complexity, operation and maintenance trouble, the unfavorable to maintain and update and so on. Design of an intelligent explosion-proof electromagnetic starting reactor based on PIC16F887 microcontroller is proposed, this reactor has time type, current type, time-current starting type which can be set and it has temperature detection protection function in the starting process. After starting completion, it also has the bypass electrical locking function which can real-time monitor the current, voltage and temperature signals to realize intelligent. Using the reactor of controller already has been applied rated voltage 10kV, rated power 1600kW fan commissioning in a coal mine, the test results indicate that this reactor controls current smoothly in the starting process, and has reliable starting performance, easy operation, and high degree of intelligence.
21
LeRon Shults, F. "Progress in simulating human geography: Assemblage theory and the practice of multi-agent artificial intelligence modeling." Progress in Human Geography 46, no. 1 (2021): 108–20. http://dx.doi.org/10.1177/03091325211059567.
Full textAbstract:
Over the last few years, there has been an explosion of interest in assemblage theory among human geographers. During this same period, a growing number of scholars in the field have utilized computational methodologies to simulate the complex adaptive systems they study. However, very little attention has been paid to the connections between these two developments. This article outlines those connections and argues that more explicitly integrating assemblage theory and computer modeling can encourage a more robust philosophical understanding of both and facilitate progress in scientific research on the ways in which complex socio-material systems form and transform.
22
Aljuwaiber, Abobakr. "Data Warehousing as Knowledge Pool : A Vital Component of Business Intelligence." International Journal of Computer Science, Engineering and Information Technology 12, no. 4 (2022): 21–26. http://dx.doi.org/10.5121/ijcseit.2022.12402.
Full textAbstract:
Increasing amounts of information and diverse formats have forced organizations to create large data repositories in response to the information explosion in the 21st century. As a result, the model of a data warehouse has been introduced to define a large data repository. The purpose of this article is to describe the principles of data warehousing in business and how it can enhance the generation of new knowledge throughout the organization. Definitions of data warehousing are considered and include methods of its use, namely query and data simulation. The steps required prior to transforming the raw data into a data warehouse and project goals for data warehouses and metadata are also discussed. The objective of this document is to provide a clear and simple description of data warehousing terms and concepts, especially for busy managers and laymen. They may only need basic and direct information about data warehouses to gain a complete understanding of the principles of the data warehouse.
23
Gonem, Sherif, Wim Janssens, Nilakash Das, and Marko Topalovic. "Applications of artificial intelligence and machine learning in respiratory medicine." Thorax 75, no. 8 (2020): 695–701. http://dx.doi.org/10.1136/thoraxjnl-2020-214556.
Full textAbstract:
The past 5 years have seen an explosion of interest in the use of artificial intelligence (AI) and machine learning techniques in medicine. This has been driven by the development of deep neural networks (DNNs)—complex networks residing in silico but loosely modelled on the human brain—that can process complex input data such as a chest radiograph image and output a classification such as ‘normal’ or ‘abnormal’. DNNs are ‘trained’ using large banks of images or other input data that have been assigned the correct labels. DNNs have shown the potential to equal or even surpass the accuracy of human experts in pattern recognition tasks such as interpreting medical images or biosignals. Within respiratory medicine, the main applications of AI and machine learning thus far have been the interpretation of thoracic imaging, lung pathology slides and physiological data such as pulmonary function tests. This article surveys progress in this area over the past 5 years, as well as highlighting the current limitations of AI and machine learning and the potential for future developments.
24
Ma, Xiliang, and Ruiqing Mao. "Path planning for coal mine robot to avoid obstacle in gas distribution area." International Journal of Advanced Robotic Systems 15, no. 1 (2018): 172988141775150. http://dx.doi.org/10.1177/1729881417751505.
Full textAbstract:
As the explosion-proof safety level of coal mine robot has not yet reached the level of intrinsic safety “ia,” therefore, path planning methods for coal mine robot to avoid the dangerous area of gas are necessary. To avoid a secondary explosion when the coal mine robot passes through gas hazard zones, a path planning method is proposed, considering the gas concentration distributions. The path planning method is composed of two steps in total: the global path planning and the local path adjustment. First, the global working path for coal mine robot is planed based on the Dijkstra algorithm and the ant colony algorithm. Second, with consideration of the dynamic environment, when hazardous gas areas distribute over the planed working path again, local path adjustments are carried out with the help of a proposed local path adjustment method. Lastly, experiments are conducted in a roadway after accident, which verify the effectiveness of the proposed path planning method.
25
Tsigelny, Igor F. "Artificial intelligence in drug combination therapy." Briefings in Bioinformatics 20, no. 4 (2018): 1434–48. http://dx.doi.org/10.1093/bib/bby004.
Full textAbstract:
AbstractCurrently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a physician often meets a patient having a genomic profile including more than five molecular aberrations. Drug combination therapy has been an area of interest for a while, for example the classical work of Loewe devoted to the synergism of drugs was published in 1928—and it is still used in calculations for optimal drug combinations. More recently, over the past several years, there has been an explosion in the available information related to the properties of drugs and the biomedical parameters of patients. For the drugs, hundreds of 2D and 3D molecular descriptors for medicines are now available, while for patients, large data sets related to genetic/proteomic and metabolomics profiles of the patients are now available, as well as the more traditional data relating to the histology, history of treatments, pretreatment state of the organism, etc. Moreover, during disease progression, the genetic profile can change. Thus, the ability to optimize drug combinations for each patient is rapidly moving beyond the comprehension and capabilities of an individual physician. This is the reason, that biomedical informatics methods have been developed and one of the more promising directions in this field is the application of artificial intelligence (AI). In this review, we discuss several AI methods that have been successfully implemented in several instances of combination drug therapy from HIV, hypertension, infectious diseases to cancer. The data clearly show that the combination of rule-based expert systems with machine learning algorithms may be promising direction in this field.
26
Wang, Fang, Yi-Zhao Li, Li-Ping Li, and De-Ren Kong. "Research on FAE Cloud Image Processing Method Based on Background Subtraction and Region Growing." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 07 (2018): 1854019. http://dx.doi.org/10.1142/s0218001418540198.
Full textAbstract:
After the first initiation, the Fuel Air Explosive (FAE) cloud formed through fuel explosion dispersal and it will generate tremendous damaging power after being detonated the second time. As the damaging power is closely related to the determination of reinitiation time, it is of great significance to study the growth principle of FAE cloud by means of analyzing FAE cloud images. Combining with background subtraction and region growing, an improved region growing image processing method was proposed, in which the seeds of region growing abstracted through background subtraction method and the growing criterion was modified. With this method, the integrate area of cloud can be obtained for extracting geometric parameters. Experiments were carried out on both cloudy and sunny days, and image overlap score was used to quantitatively evaluate the accuracy of images segmentation. The result indicated that this image processing method has advantages of high precision and robustness. In addition, the computation burden is reduced significantly compared with traditional region growing method.
27
Qiu, Hang, Shuhan Ding, Jianbo Liu, Liya Wang, and Xiaodong Wang. "Applications of Artificial Intelligence in Screening, Diagnosis, Treatment, and Prognosis of Colorectal Cancer." Current Oncology 29, no. 3 (2022): 1773–95. http://dx.doi.org/10.3390/curroncol29030146.
Full textAbstract:
Colorectal cancer (CRC) is one of the most common cancers worldwide. Accurate early detection and diagnosis, comprehensive assessment of treatment response, and precise prediction of prognosis are essential to improve the patients’ survival rate. In recent years, due to the explosion of clinical and omics data, and groundbreaking research in machine learning, artificial intelligence (AI) has shown a great application potential in clinical field of CRC, providing new auxiliary approaches for clinicians to identify high-risk patients, select precise and personalized treatment plans, as well as to predict prognoses. This review comprehensively analyzes and summarizes the research progress and clinical application value of AI technologies in CRC screening, diagnosis, treatment, and prognosis, demonstrating the current status of the AI in the main clinical stages. The limitations, challenges, and future perspectives in the clinical implementation of AI are also discussed.
28
Dupin-Bryant, Pamela A., and David H. Olsen. "Business Intelligence, Analytics And Data Visualization: A Heat Map Project Tutorial." International Journal of Management & Information Systems (IJMIS) 18, no. 3 (2014): 185. http://dx.doi.org/10.19030/ijmis.v18i3.8705.
Full textAbstract:
Business intelligence and analytics (BI&A) initiatives are helping countless organizations harness and interpret the vast amount of information available in the world today. The explosion of BI&A in industry has fueled the high demand for knowledge workers with advanced analytical skills. The purpose of this paper is to introduce a data visualization project tutorial for Information Systems (IS) education. The applied BI&A tutorial was designed to help students learn how to create and analyze a heat map using SQL Server Data Tools (SSDT) and SQL Server Reporting Services (SSRS). Students learn how to make decisions based on large amounts of data by presenting it in visual form. This tutorial exposes students to the decision-making power derived from data visualization. Utilizing the 5E Instructional Model, the tutorial assists in the development of BI&A professionals who can quickly make sense of mass amounts of data, identify trends buried within data sets, and are skilled in making sound decisions that add value to organizations.
29
Gong, Chibing. "Dynamic Search Fireworks Algorithm with Adaptive Parameters." International Journal of Ambient Computing and Intelligence 11, no. 1 (2020): 115–35. http://dx.doi.org/10.4018/ijaci.2020010107.
Full textAbstract:
As a comparatively new algorithm of swarm intelligence, the dynamic search fireworks algorithm (dynFWA) imitates the explosion procedure of fireworks. With the goal of achieving global optimization and further boosting performance of dynFWA, adaptive parameters are added in this present study, called dynamic search fireworks algorithm with adaptive parameters (dynFWAAP). In this novel dynFWAAP, a self-adaptive method is used to tune the amplification coefficient Ca and the reduction coefficient Cr for fast convergence. To balance exploration and exploitation, the coefficient of amplitude α and the coefficient of sparks β are also adapted, and a new selection operator is proposed. Evaluated on twelve benchmark functions, it is evident from the experimental results that the dynFWAAP significantly outperformed the three variants of fireworks algorithms (FWA) based on solution accuracy and performed best in other four algorithms of swarm intelligence in terms of time cost and solution accuracy.
30
Zavagno, D., and G. Caputo. "Two New Dynamic Effects: Light Explosion and Night Crash." Perception 26, no. 1_suppl (1997): 56. http://dx.doi.org/10.1068/v970267.
Full textAbstract:
Starting from an achromatic display used by Zavagno to study a glare and a ‘smoke’ effect, we show two new dynamic effects that we call (a) ‘light explosion’ and (b) ‘night crash’. On a uniform white or black background four black or white rectangles (inducers, 1 deg × 5.7 deg) were arranged to form an orthogonal cross with a square gap in its centre. (a) When the luminance of black inducers on a white background is transformed into a smooth gray scale gradient with the lighter ends facing the square gap, a luminous mist with a glare effect is seen. When such a transformation is performed dynamically by changing the gradient from outside to inside (with the outside ends remaining black and the inside changing toward white), a sudden explosion of light is seen. (b) When the luminance of white inducers on a black background is transformed into a smooth gray scale gradient with their darker ends facing the square gap, a sort of dark ‘smoke’ is seen. If such a transformation is performed dynamically by changing the gradient from inside to outside (with the outside ends remaining white and the inside changing toward black), a sudden and instantaneous black diffusion (a sort of night crash) is seen. Both the light explosion and the night crash effects have an exponential course followed by an immediate drop. Psychophysical data show that both effects depend on an interaction between the lightness of the background, the lightness of the square gap, and the transformation rate of the gray scale gradient.
31
Chen, Xu, Xuan Wei, Guanxue Yang, and Wenli Du. "Fireworks explosion based artificial bee colony for numerical optimization." Knowledge-Based Systems 188 (January 2020): 105002. http://dx.doi.org/10.1016/j.knosys.2019.105002.
Full text
32
Simen, Patrick. "Preventing combinatorial explosion in a localist, neural network architecture using temporal synchrony." Connection Science 23, no. 2 (2011): 131–44. http://dx.doi.org/10.1080/09540091.2011.570741.
Full text
33
Yan, Bin, Qing Chen, Run Ye, and Xiaojia Zhou. "Insulator detection and recognition of explosion based on convolutional neural networks." International Journal of Wavelets, Multiresolution and Information Processing 17, no. 02 (2019): 1940008. http://dx.doi.org/10.1142/s0219691319400083.
Full textAbstract:
Unmanned aerial vehicles (UAVs) equipped with high definition (HD) cameras can obtain a large number of detailed inspection images. The insulator is an indispensable component in the transmission lines. Detecting insulator in image video quickly and accurately can provide a reliable basis for the ranging and the obstacle avoidance flight of UAV close to the tower and transmission line. At the same time, the insulator is a serious threat to the safety of the power grid due to the multiple faults of the insulator, and the computer technology should be fully utilized to diagnose the fault. Detection of the insulator images with the complex aerial background is implemented by constructing a convolutional neural network (CNN), which has the classic architecture of five modules of convolution and pooling, two modules of fully connected layers. In this paper, we propose a recognition algorithm for explosion fault based on saliency detection, which uses the trained network model to extract the features. Then, we put the saliency maps into a self-organizing feature map (SOM) network and build the mathematical module via super pixel segmentation, contour detection and other image processing methods. The test shows that the algorithm can reduce the error that may be caused by manual analysis. It also demonstrates that the detection of the insulator and the recognition of explosion fault can effectively improve the efficiency and intelligence level.
34
Moss, Henry. "Genes, Affect, and Reason." Techné: Research in Philosophy and Technology 20, no. 1 (2016): 1–15. http://dx.doi.org/10.5840/techne20162443.
Full textAbstract:
Many believe that, in addition to cognitive capacities, autonomous robots need something similar to affect. As in humans, affect, including specific emotions, would filter robot experience based on a set of goals, values, and interests. This narrows behavioral options and avoids combinatorial explosion or regress problems that challenge purely cognitive assessments in a continuously changing experiential field. Adding human-like affect to robots is not straightforward, however. Affect in organisms is an aspect of evolved biological systems, from the taxes of single-cell organisms to the instincts, drives, feelings, moods, and emotions that focus human behavior through the mediation of hormones, pheromones, neurotransmitters, the autonomic nervous system, and key brain structures. We argue that human intelligence is intimately linked to biological affective systems and to the unique repertoire of potential behaviors, sometimes conflicting, they facilitate. Artificial affect is affect in name only and without genes and biological bodies, autonomous robots will lack the goals, interests, and value systems associated with human intelligence. We will take advantage of their general intelligence and expertise, but robots will not enter our intellectual world or apply for legal status in the community.
35
YADAV, PARTH, AMAN YADAV, and RASHMI AGRAWAL. "Use of Artificial Intelligence in the Real World." International Journal of Computer Science and Mobile Computing 11, no. 12 (2022): 83–90. http://dx.doi.org/10.47760/ijcsmc.2022.v11i12.008.
Full textAbstract:
Artificial Intelligence is a significant innovation that is an important part of our day-to-day lives as well as our industry. Today, artificial intelligence is a rapidly advancing innovation in our daily lives. From the Innovation Industry to ordinary people, it will change the way of life. A human's state is updated by the AI at every point in their lives. As an example, a school today uses AI programming to enable participation based on face recognition. In the future, driverless cars will be the best. Vehicles are completely constrained by the AI programming that detects signs and street points. In most ICT models, enormous amounts of information are incorporated, self-thought capability is not addressed, and there is a lot of confusion. There is an explosion of creative innovations, such as corporate collaboration and profound learning. As AI frameworks learn to adapt to individuals' character and goals, individuals' future relationships with machines will always become contact, liquid, and customized. As a result of these AI applications, individuals will be able to monitor their wellbeing, be alerted to risks in advance, and receive administrations when they need them. While AI continues to bring significant benefits in every field, it also raises significant moral and social issues, such as security issues. A number of occupations have already been dislodged due to robotics and other artificial intelligence advancements. In this paper, we focus on the more extensive and smaller scope of man-made consciousness, its shrewd gadgets, and future advancements. Additionally, this paper shed a few light on how man-made brainpower is used in the day-to-day world.
36
Ninan, Jacob, B. A. A. Sai Kumar, and R. J. Padodara. "A Glimpse into Artificial Intelligence in Animal Physiology and Allied Sciences." Animal Reproduction Update 2, no. 1 (2022): 72–81. http://dx.doi.org/10.48165/aru.2022.2104.
Full textAbstract:
Artificial Intelligence (AI) has developed as an interdisciplinary science based on computers and is concerned with building machines and equipment which use human intelligence to perform a particular task. The role of AI is manifold in our day-to-day lives. With high penetration amongst people in different societies, AI has transformed the way of living and has the potential to act as a vehicle to disseminate information regarding animal health, production, and reproduction aspects. AI has already made an immense contribution in veterinary and allied sciences by helping in devising various applications used in research and simulation aids. In addition, it has been put in to use efficiently in the field of veterinary sciences thereby hastening diagnosis, treatment, and prognosis of various animal diseases. The history of AI, its applications as software packages in statistics, bioinformatics, simulation apps, and a list of various equipment used for analytical, clinical, and livestock farm purposes are elaborated in this article. Despite playing a vital role, AI has to be further refined in such a way to target the rural livestock farmers to improve animal health and production in developing countries that are in dire need of meeting food security requirements amidst the current scenario of population explosion.
37
Jia, Tiejun, Cheng Wang, Zhiqiang Tian, Bingyin Wang, and Feng Tian. "Design of Digital and Intelligent Financial Decision Support System Based on Artificial Intelligence." Computational Intelligence and Neuroscience 2022 (June 20, 2022): 1–7. http://dx.doi.org/10.1155/2022/1962937.
Full textAbstract:
The quality of financial decision-making is very important to the future development of an enterprise, but it is often affected by the completeness of useful information for decision-making and the subjective factors of decision makers, and is often unstable. With the development of computer technology, the financial decision support system came into being, which improved the quality of financial decision to some extent. However, although the existing financial decision support system has achieved dataization to a certain extent, it still faces problems such as artificial leadership, insufficient intelligence, and poor decision-making efficiency, and cannot fully meet the needs of decision-makers. The explosion of artificial intelligence technology in recent years has provided potential improvements to financial decision support systems. In this article, we conduct a detailed analysis of the deficiencies in the current financial decision support system, build the mechanism and implementation path of the financial decision support system under artificial intelligence, and design a digital and intelligent financial decision support system. At the same time, we apply the proposed financial decision support system to the financial practice of X enterprise. Through the questionnaire survey, it is found that through the comprehensive application of artificial intelligence technology, the new system has a higher degree of intelligence than the existing system, and its construction can effectively improve the timeliness and accuracy of financial decision-making, while reducing the cost of financial decision-making. It is conducive to promoting the integration of management accounting and financial accounting.
38
Dabbous, Amal, and Nada Mallah Boustani. "Digital Explosion and Entrepreneurship Education: Impact on Promoting Entrepreneurial Intention for Business Students." Journal of Risk and Financial Management 16, no. 1 (2023): 27. http://dx.doi.org/10.3390/jrfm16010027.
Full textAbstract:
This study aims to examine the effect of entrepreneurship education and artificial intelligence (AI) development on entrepreneurial intentions while investigating the mediating role of perceived behavioral control. The proposed model also accounts for individual and contextual socioeconomic factors. This study tries to fill the gap in the entrepreneurship literature, which is still lacking with respect to the impact of new technologies on entrepreneurship intentions and shows conflicting results regarding the influence of entrepreneurship education. Our study surveyed 223 business students in Lebanon. The context of this study is of high importance, particularly since the country is currently facing a deep, multifaced political, economic, and financial crisis, and entrepreneurship might be considered an important channel for generating basic sources of income, steering the recovery process, and increasing Lebanese resilience against this highly unstable economy. The structural equation modeling technique (SEM) was conducted to validate the hypotheses. The results show that perceived behavioral control fully mediates the relations between performance expectancy of AI solutions, entrepreneurship education, and entrepreneurial intention. Risk aversion and social support exert a direct impact on entrepreneurial intentions. The findings highlight the need to account for entrepreneurship education and AI development when analyzing entrepreneurial intentions.
39
Jasiulek, Dariusz, Krzysztof Stankiewicz, and Mariusz Woszczyński. "Intelligent Self-Powered Sensors in the State-of-the-Art Control Systems of Mining Machines." Archives of Mining Sciences 61, no. 4 (2016): 907–15. http://dx.doi.org/10.1515/amsc-2016-0060.
Full textAbstract:
Abstract Perspectives of development of control system dedicated for areas threatened by methane and/or coal dust explosion hazard are presented. Development of self-powered sensors, dedicated for operation in wireless network is one of the development directions. Such a solution will complement typical control systems and it can be used in the places, where there is no possibility of using the typical sensors, in close vicinity to the machine – due to lack of wired connection. General concept of the self-powered sensors with use of two methods of power supply – piezoelectric energy harvester and thermoelectric generator, is given. Perspective of using the methods of artificial intelligence in automatic configuration of sensors network is suggested.
40
Jones, Matthew L. "How We Became Instrumentalists (Again)." Historical Studies in the Natural Sciences 48, no. 5 (2018): 673–84. http://dx.doi.org/10.1525/hsns.2018.48.5.673.
Full textAbstract:
In the last two decades, a highly instrumentalist form of statistical and machine learning has achieved an extraordinary success as the computational heart of the phenomenon glossed as “predictive analytics,” “data mining,” or “data science.” This instrumentalist culture of prediction emerged from subfields within applied statistics, artificial intelligence, and database management. This essay looks at representative developments within computational statistics and pattern recognition from the 1950s onward, in the United States and beyond, central to the explosion of algorithms, techniques, and epistemic values that ultimately came together in the data sciences of today. This essay is part of a special issue entitled Histories of Data and the Database edited by Soraya de Chadarevian and Theodore M. Porter.
41
Ryan, M. R. K. "Exploiting Subgraph Structure in Multi-Robot Path Planning." Journal of Artificial Intelligence Research 31 (March 28, 2008): 497–542. http://dx.doi.org/10.1613/jair.2408.
Full textAbstract:
Multi-robot path planning is difficult due to the combinatorial explosion of the search space with every new robot added. Complete search of the combined state-space soon becomes intractable. In this paper we present a novel form of abstraction that allows us to plan much more efficiently. The key to this abstraction is the partitioning of the map into subgraphs of known structure with entry and exit restrictions which we can represent compactly. Planning then becomes a search in the much smaller space of subgraph configurations. Once an abstract plan is found, it can be quickly resolved into a correct (but possibly sub-optimal) concrete plan without the need for further search. We prove that this technique is sound and complete and demonstrate its practical effectiveness on a real map. A contending solution, prioritised planning, is also evaluated and shown to have similar performance albeit at the cost of completeness. The two approaches are not necessarily conflicting; we demonstrate how they can be combined into a single algorithm which outperforms either approach alone.
42
MAKRIS, DIMITRIOS, GEORGIOS BARDIS, GEORGIOS MIAOULIS, and DIMITRI PLEMENOS. "ACQUISITION AND EXPLOITATION OF QUALITATIVE ASPECTS IN 3D SCENE SYNTHESIS." International Journal on Artificial Intelligence Tools 18, no. 01 (2009): 39–59. http://dx.doi.org/10.1142/s0218213009000032.
Full textAbstract:
The aim of this paper is to tackle the problem of combinatorial explosion which is inherent in declarative three-dimensional scene synthesis. This is achieved by encoding desired qualitative aspects, not originally supported by the Declarative Modeling methodology, and applying them to the Solution Generation and/or Scene Understanding phase(s), in order to provide the designer with a subset of solutions, which are most representative of the aforementioned aspects. For this reason, we have adapted and applied a machine learning technique, as well as an evolutionary search method, to the current context. The former refers to the gradual construction of a preference model, comprising an incrementally learning mechanism based on actual designer solution evaluation during regular system use. The latter approach models qualitative aspects through a multi-objective genetic algorithm variation based on weighted sums. The algorithm is applied during the generation and understanding phases of Declarative Modeling. The experimental results provide evidence of successful acquisition and exploitation of the desired qualitative characteristics in the paradigm of declarative three-dimensional scene synthesis.
43
Gotlieb, Arnaud, Dusica Marijan, and Helge Spieker. "ITE: A Lightweight Implementation of Stratified Reasoning for Constructive Logical Operators." International Journal on Artificial Intelligence Tools 29, no. 03n04 (2020): 2060006. http://dx.doi.org/10.1142/s0218213020600064.
Full textAbstract:
Constraint Programming (CP) is a powerful declarative programming paradigm where inference and search are interleaved to find feasible and optimal solutions to various type of constraint systems. However, handling logical connectors with constructive information in CP is notoriously difficult. This paper presents If Then Else (ITE), a lightweight implementation of stratified constructive reasoning for logical connectives. Stratification is introduced to cope with the risk of combinatorial explosion of constructing information from nested and combined logical operators. ITE is an open-source library built on top of SICStus Prolog clpfd, which proposes various operators, including constructive disjunction and negation, constructive implication and conditional. These operators can be used to express global constraints and to benefit from constructive reasoning for more domain pruning during constraint filtering. Even though ITE is not competitive with specialized filtering algorithms available in some global constraints implementations, its expressiveness allows users to easily define well-tuned constraints with powerful deduction capabilities. Our extended experimental results show that ITE is more efficient than available generic approaches that handle logical constraint systems over finite domains.
44
Rehman, Amjad, Tanzila Saba, Khalid Haseeb, Souad Larabi Marie-Sainte, and Jaime Lloret. "Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing." Energies 14, no. 19 (2021): 6414. http://dx.doi.org/10.3390/en14196414.
Full textAbstract:
Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems.
45
Utomo, Chandra Eko wahyudi. "Implementasi Bussiness Intelligent dalam e-Tourism Berbasis Big Data." Journal of Tourism and Creativity 3, no. 2 (2019): 163. http://dx.doi.org/10.19184/jtc.v3i2.14065.
Full textAbstract:
Abstract
 The use of information technology that is integrated with work processes in an organization has become an absolute necessity. The availability of complete, correct and accurate data and information has become a basic requirement for the survival of an organization. Business Intelligence (BI) is a form of implementation that is able to answer the above needs. BI has been widely used by organizations in managing data and information to support decision making. BI is usually associated with efforts to maximize the performance of an organization. Business Intelligence System is a term that is generally used for the type of application or technology used to assist BI activities, such as collecting data, providing access, and analyzing data and information about company performance. Along with the rapid online-based information systems including e-tourism, creating a huge data explosion on the internet (bigdata). The very high growth of tourism data on the internet can be utilized for the needs of the tourism industry and research needs in the field of tourism.
 Keywords: intelligent business, e-tourism, big data
46
Acernese, F., A. Ciaramella, S. De Martino, R. De Rosa, M. Falanga, and R. Tagliaferri. "Neural networks for blind-source separation of Stromboli explosion quakes." IEEE Transactions on Neural Networks 14, no. 1 (2003): 167–75. http://dx.doi.org/10.1109/tnn.2002.806649.
Full text
47
DE JONG, HIDDE. "Qualitative simulation and related approaches for the analysis of dynamic systems." Knowledge Engineering Review 19, no. 2 (2004): 93–132. http://dx.doi.org/10.1017/s0269888904000177.
Full textAbstract:
Methods for qualitative simulation allow predictions on the dynamics of a system to be made in the absence of quantitative information, by inferring the range of possible qualitative behaviors compatible with the structure of the system. This article reviews QSIM and other qualitative simulation methods. It discusses two problems that have seriously compromised the application of these methods to realistic problems in science and engineering: the occurrence of spurious behavior predictions and the combinatorial explosion of the number of behavior predictions. In response to these problems, related approaches for the qualitative analysis of dynamic systems have emerged: qualitative phase-space analysis and semi-quantitative simulation. The article argues for a synthesis of these approaches in order to obtain a computational framework for the qualitative analysis of dynamic systems. This should provide a solid basis for further upscaling and for the development of model-based reasoning applications of a wider scope.
48
Zheng, Jian-Guo, Chao-Qun Zhang, and Yong-Quan Zhou. "Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/739437.
Full textAbstract:
Artificial bee colony (ABC) algorithm is a popular swarm intelligence technique inspired by the intelligent foraging behavior of honey bees. However, ABC is good at exploration but poor at exploitation and its convergence speed is also an issue in some cases. To improve the performance of ABC, a novel ABC combined with grenade explosion method (GEM) and Cauchy operator, namely, ABCGC, is proposed. GEM is embedded in the onlooker bees’ phase to enhance the exploitation ability and accelerate convergence of ABCGC; meanwhile, Cauchy operator is introduced into the scout bees’ phase to help ABCGC escape from local optimum and further enhance its exploration ability. Two sets of well-known benchmark functions are used to validate the better performance of ABCGC. The experiments confirm that ABCGC is significantly superior to ABC and other competitors; particularly it converges to the global optimum faster in most cases. These results suggest that ABCGC usually achieves a good balance between exploitation and exploration and can effectively serve as an alternative for global optimization.
49
Menger, Fredric M. "An Alternative Molecular View of Evolution: How DNA was Altered over Geological Time." Molecules 25, no. 21 (2020): 5081. http://dx.doi.org/10.3390/molecules25215081.
Full textAbstract:
Four natural phenomena are cited for their defiance of conventional neo-Darwinian analysis: human intelligence; cat domesticity; the Cambrian explosion; and convergent evolution. 1. Humans are now far more intelligent than needed in their hunting–gathering days >10,000 years ago. 2. Domestic cats evolved from wildcats via major genetic and physical changes, all occurring in less than 12,000 years. 3. The Cambrian explosion refers to the remarkable expansion of species that mystifies evolutionists, as there is a total lack of fossil evidence for precursors of this abundant new life. 4. Convergent evolution often involves formation of complex, multigene traits in two or more species that have no common ancestor. These four evolutionary riddles are discussed in terms of a proposed “preassembly” mechanism in which genes and gene precursors are collected silently and randomly over extensive time periods within huge non-coding sections of DNA. This is followed by epigenetic release of the genes, when the environment so allows, and by natural selection. In neo-Darwinism, macroevolution of complex traits involves multiple mutation/selections, with each of the resulting intermediates being more favorable to the species than the previous one. Preassembly, in contrast, invokes natural selection only after a partially or fully formed trait is already in place. Preassembly does not supplant neo-Darwinism but, instead, supplements neo-Darwinism in those important instances where the classical theory is wanting.
50
Huang, Zhiqiang, Lei He, Xinxia Li, Yewei Kang, and Dou Xie. "Depth control for storage tank in-service inspection robot based on artificial intelligence control." Industrial Robot: An International Journal 45, no. 6 (2018): 732–43. http://dx.doi.org/10.1108/ir-05-2018-0085.
Full textAbstract:
Purpose The purpose of this paper is to propose a buoyancy-gravity adjustment device and a fuzzy intelligent controller for the depth control of a storage tank in-service inspection robot. Design/methodology/approach The structure of the robot is first designed based on the construction of the bottom of a crude oil tank and explosion-proof requirements. The buoyancy-gravity adjustment system is used to control the vertical movement of the robot. The motion analysis of the robot indicates that the diving or rising process is influenced by hydrodynamic force and umbilical cord tension. Considering the nonlinear model in-depth control, a fuzzy intelligent controller is proposed to address the depth control problem. The primary fuzzy controller is used to compensate for initial error with fast response. The secondary fuzzy controller is activated by an intelligent switch to eliminate the steady error. Findings The proposed fuzzy controller can better solve the complicated hydrodynamic problem of the coupling of umbilical cord and the robot during depth control by classifying the error values of depth, velocity and acceleration. Originality/value The buoyancy-gravity adjustment device and the depth control system of the robot can move through the heating coils by safe and accurate diving or rising.