Kongzhi yu Juece/Control and Decision

Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) is a monthly peer-reviewed scopus indexed journal originally founded in 1986. It is sponsored by the Ministry of Education, china and Northeastern University, china. Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) has always adhered to the correct purpose of running the journal, and has been committed to gathering and disseminating excellent academic achievements, inspiring technological innovation, and promoting the development of disciplines in my country.Aiming at major national needs and international frontiers, this journal has published a large number of original and high-level research result. The journal was selected into the "China Science and Technology Journal Excellence Action Plan Project" in December 2019.In the future, it will strive to build an open innovation, collaborative integration.

Aim and Scope

Kongzhi yu Juece/Control and Decision

Computer Science and Engineering: Lizi Jiaohuan Yu Xifu/Ion Exchange and Adsorption Fa yi xue za zhi

Software Engineering, Data Security, Computer Vision, Image Processing, Cryptography, Computer Networking, Database system and Management, Data mining, Big Data, Robotics, Parallel and distributed processing, Artificial Intelligence, Natural language processing , Neural Networking, Distributed Systems , Fuzzy logic, Advance programming, Machine learning, Internet & the Web, Information Technology, Computer architecture, Virtual vision and virtual simulations, Operating systems, Cryptosystems and data compression, Security and privacy, Algorithms, Sensors and ad-hoc networks, Graph theory, Pattern/image recognition, Neural networks,

Electrical Engineering and Telecommunication Section:

Electrical Engineering, FACTS devices , Insulation systems , Power quality , Telecommunication Engineering, Electro-mechanical System Engineering, Biological Biosystem Engineering, Integrated Engineering, Electronic Engineering, Hardware-software co-design and interfacing, Semiconductor chip, Peripheral equipments, Nanotechnology, Advanced control theories and applications, Machine design and optimization , Turbines micro-turbines, High voltage engineering, Electrical actuators , Energy optimization , Electric drives , Electrical machines, HVDC transmission, Power electronics.

Mechanical and Materials Engineering :

kinematics and dynamics of rigid bodies, theory of machines and mechanisms, vibration and balancing of machine parts, stability of mechanical systems, mechanics of continuum, strength of materials, fatigue of materials, hydromechanics, aerodynamics, thermodynamics, heat transfer, thermo fluids, nanofluids, energy systems, renewable and alternative energy, engine, fuels,

Chemical Engineering :

Chemical engineering fundamentals, Particulate systems, Rheology, Physical, Theoretical and Computational Chemistry, Chemical engineering educational challenges and development, Chemical reaction engineering, Multifase flows, Chemical engineering equipment design and process design, Thermodynamics, Catalysis & reaction engineering, Interfacial & colloidal phenomena, Transport phenomena in porous/granular media, Membranes and membrane science, Crystallization, distillation, absorption and extraction, Ionic liquids/electrolyte solutions.

Mathematics :

Actuarial science, Algebra, Algebraic geometry, Analysis and advanced calculus, Approximation theory, Boundry layer theory, Calculus of variations, Combinatorics, Complex analysis, Continuum mechanics, Cryptography, Demography, Differential equations, Differential geometry, Dynamical systems, Econometrics, Fluid mechanics, Functional analysis, Game theory, General topology, Geometry, Graph theory, Group theory, Information theory, Industrial mathematics, Integral transforms and integral equations, Lie algebras, Magnetohydrodynamics, Mathematical analysis, Logic,

Physics Section :

Astrophysics, Atomic and molecular physics, Biophysics, Chemical physics, Civil engineering physics, Cluster physics, Computational physics, Condensed matter, Cosmology, Device physics, Fluid dynamics, Geophysics. High energy particle physics, Laser, Mechanical engineering, Medical physic, Nanotechnology, Nonlinear science, Nuclear physics, Optics, Photonics, Plasma and fluid physics, Quantum physics, Magnetohydrodynamics, Robotics, Soft matter and polymers,

// Latest Journals

A sparse learning method for SCN soft measurement model

For the stochastic configuration network (SCN), it randomly produces the hidden parameters and adaptively selects their scopes using an inequality constraint. As a result, the SCN exhibits superior performance in convergence speed and modeling accuracy- low. value and redundant hidden nodes due to the inherent feature of a randomized algorithm. To improve the sparsity of the SCN soft sensor model, a parsimonious stochastic configuration network (PSCN) is proposed in this paper. The L 1 norm is plugged into the cost function of the PSCN, and a new inequality constraint is built to obtain the

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Path-following control of an AUV in cascade under input saturation

This paper studies the problem of spatial path-following control of underactuated autonomous underwater vehicles (AUVs) with multiple uncertainties and input saturation taken into account. Initially, the reduced-order extended state observes (ESOs) is introduced to estimate and compensate all humped uncertainties due to the model parameters perturbations, unmodeled dynamics, environmental disturbances and nonlinear hydrodynamic damping terms. Furthermore, the spatial path-following control strategy is established by combining with backstepping, integral sliding mode control and estimator to

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A survey on multimodal multiobjective optimization

Multimodal multi-objective problems (MMOPs) commonly arise in real-world problems where distant solutions in decision space correspond to very similar objective values. To obtain more Pareto optimal solutions for MMOPs, many multimodal multi-objective evolutionary algorithms (MMEAs) have been proposed. For now, few studies have encompassed most of the recently proposed representative MMEAs and made a comparative comparison. In this study, we first review the related works during the last two decades. Then, we choose 12 stateof-the-art algorithms that utilize different diversity-maintaining

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A path planning algorithm of deterministic mobile robot based on immune

Aiming at the problems of low efficiency of path planning, a new node storage structure is introduced and the search method is optimized to improve the deterministic iterative path planning algorithm. First, the number of antibodies is determined based on the connectable starting path point, when generating the initial antibody with the inspiration of the optimal angle vaccine. Then, the connectable path point of the starting point is treated as the root node to rebuild the new path with path filtering by means of the optimal path fit value. The initial optimal antibody is used as the scree

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Parameter optimization of BP neural network based on coyote optimization algorithm with inverse time chaotic

A chaotic coyote optimization algorithm based on inverse time-decay operator(ICCOA) is proposed to solve the coyote optimization algorithm(COA), such as the poor performance and low diversity. Firstly, the inverse time decay weight factor is added in the process of individual iterative updating, so as to maintain the balance between global search and local development ability and improve the search speed of the algorithm. Secondly, add the chaotic interference mechanism based on Tent chaotic map, some poor individuals in the population were mapped to produce new individuals, thus increasing

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